The transfer of the medical care services to the patient, rather than the transport of the patient to the
medical services providers is aim of the project. This is achieved by using web-based applications including
Modern Medical Informatics Services which is easier, faster and less expensive. The required system
implements the suitable informatics and electronics solutions efficiently for the Tele-medicine care. We
proposed an approach to manage different multimedia medical databases in the telemedicine system. In
order to be efficiently and effectively manage, search, and display database information, we define an
information package for both of doctor and patient as a concise data set of their medical information from
each visit. The methodology for accessing various types of medical records will be provided, also we will
design two web-based interfaces, high-quality data and display for many medical service purposes.
A clinical information system (CIS) is a technology-based system used at the point of care to support the acquisition, processing, storage, and sharing of patient information across locations. Key components of a CIS include the type of application, number of users, where data is stored, and backup procedures. Implementation requires input from medical staff, IT, and management to ensure accuracy, privacy, and system reliability. Larger healthcare facilities can expect to pay $10 million to $1 billion to establish a CIS, with annual maintenance fees of $1 million or more.
Evaluation of a clinical information system (cis)nikita024
Â
This power point presentation provides an overview of a clinical information system (CIS). It discusses what a CIS is, how CIS have evolved, and the key players involved in designing CIS. It also examines the electronic health record component of a CIS and discusses the eight basic components that make up an EHR. Additional topics covered include clinical decision making systems, safety, costs, and education regarding CIS. The presentation was created by four students with each student covering specific slides and aspects of the topic.
PACS (Picture Archive and Communication Systems) are digital systems used to store, view, and manage diagnostic imaging studies. They allow for faster access to images compared to traditional film, which can improve patient care. While initial implementation of PACS is costly, studies have shown cost savings from reduced lost images, repeated exams, and shorter hospital stays. PACS integrate with other hospital information systems and allow multiple providers to view images simultaneously from different locations. This improves care coordination and patient discussions. Overall, PACS aim to make healthcare delivery more effective and efficient through electronic access and sharing of diagnostic images.
This quality improvement project aimed to enhance clinical data sharing between an emergency department and community health center treating homeless patients. An assessment found the organizations currently shared some electronic health data but the health center lacked access to patient summary data from the hospital. A clinical data integration plan was then developed to modify their electronic medical record systems and improve access to accurate medical information across sites of care for homeless individuals.
Health informatics is the interdisciplinary study of how to design, develop, apply and use information technology in healthcare to improve health services. It involves optimizing the acquisition, storage, retrieval and use of health information. Key applications include translational bioinformatics, clinical research informatics, clinical informatics, consumer health informatics and public health informatics. Health informatics uses mathematics and statistics to understand health data and probabilistic methods to determine clinical probabilities and integrate new data.
Cis evaluation final_presentation, nur 3563 sol1SBU
Â
An overview of a Computer Information System (CIS) and considerations that need to be taken with implementing an Electronic Health Record (EHR) in a healthcare setting.
Team Sol2 01 Health Care Informatics Power PointMessner Angie
Â
The document discusses clinical information systems and their components. It provides an overview of electronic health records and describes key parts of a clinical information system including health information, order entry, decision support, and clinical documentation. It also discusses clinical decision making systems and their importance in reducing variation, costs, and improving diagnosis. Safety, education and costs related to clinical information systems are also evaluated.
The objective of our study is to focus on the basic concepts of the medical information systems used for the management of IT information taking place in a hospital center and to share the information in databases depending on its use [2]. Nowadays, many softwares exist for the management of information in a hospital. The professional applications are oriented towards invoicing and accounting, while our application focuses on the systems used in a hospital center such as system of medical services, accounting system, storage system, human resources system, and administrative system (Figure 1)... These systems are considered as subsystems which make up the global system [1]. Our hospital information system is based on different the subsystems for the management of: laboratory results, clinic, images, pharmalogical, and pathological results[8]... So, this rate of huge information must be handled by a database management system like SQL [4,5], and its concept must be detailed using a language like UML [6]. In addition, the graphical user interface (gui) [19] is essential to complete our work, by using the software Visual Basic [10, 11], in order to achieve our software the manipulation of data must have a calibration between the execution time and the amount of data storage[14,15,20]. Hence, the distribution of databases is done according to their rate of use is an encouraging solution
A clinical information system (CIS) is a technology-based system used at the point of care to support the acquisition, processing, storage, and sharing of patient information across locations. Key components of a CIS include the type of application, number of users, where data is stored, and backup procedures. Implementation requires input from medical staff, IT, and management to ensure accuracy, privacy, and system reliability. Larger healthcare facilities can expect to pay $10 million to $1 billion to establish a CIS, with annual maintenance fees of $1 million or more.
Evaluation of a clinical information system (cis)nikita024
Â
This power point presentation provides an overview of a clinical information system (CIS). It discusses what a CIS is, how CIS have evolved, and the key players involved in designing CIS. It also examines the electronic health record component of a CIS and discusses the eight basic components that make up an EHR. Additional topics covered include clinical decision making systems, safety, costs, and education regarding CIS. The presentation was created by four students with each student covering specific slides and aspects of the topic.
PACS (Picture Archive and Communication Systems) are digital systems used to store, view, and manage diagnostic imaging studies. They allow for faster access to images compared to traditional film, which can improve patient care. While initial implementation of PACS is costly, studies have shown cost savings from reduced lost images, repeated exams, and shorter hospital stays. PACS integrate with other hospital information systems and allow multiple providers to view images simultaneously from different locations. This improves care coordination and patient discussions. Overall, PACS aim to make healthcare delivery more effective and efficient through electronic access and sharing of diagnostic images.
This quality improvement project aimed to enhance clinical data sharing between an emergency department and community health center treating homeless patients. An assessment found the organizations currently shared some electronic health data but the health center lacked access to patient summary data from the hospital. A clinical data integration plan was then developed to modify their electronic medical record systems and improve access to accurate medical information across sites of care for homeless individuals.
Health informatics is the interdisciplinary study of how to design, develop, apply and use information technology in healthcare to improve health services. It involves optimizing the acquisition, storage, retrieval and use of health information. Key applications include translational bioinformatics, clinical research informatics, clinical informatics, consumer health informatics and public health informatics. Health informatics uses mathematics and statistics to understand health data and probabilistic methods to determine clinical probabilities and integrate new data.
Cis evaluation final_presentation, nur 3563 sol1SBU
Â
An overview of a Computer Information System (CIS) and considerations that need to be taken with implementing an Electronic Health Record (EHR) in a healthcare setting.
Team Sol2 01 Health Care Informatics Power PointMessner Angie
Â
The document discusses clinical information systems and their components. It provides an overview of electronic health records and describes key parts of a clinical information system including health information, order entry, decision support, and clinical documentation. It also discusses clinical decision making systems and their importance in reducing variation, costs, and improving diagnosis. Safety, education and costs related to clinical information systems are also evaluated.
The objective of our study is to focus on the basic concepts of the medical information systems used for the management of IT information taking place in a hospital center and to share the information in databases depending on its use [2]. Nowadays, many softwares exist for the management of information in a hospital. The professional applications are oriented towards invoicing and accounting, while our application focuses on the systems used in a hospital center such as system of medical services, accounting system, storage system, human resources system, and administrative system (Figure 1)... These systems are considered as subsystems which make up the global system [1]. Our hospital information system is based on different the subsystems for the management of: laboratory results, clinic, images, pharmalogical, and pathological results[8]... So, this rate of huge information must be handled by a database management system like SQL [4,5], and its concept must be detailed using a language like UML [6]. In addition, the graphical user interface (gui) [19] is essential to complete our work, by using the software Visual Basic [10, 11], in order to achieve our software the manipulation of data must have a calibration between the execution time and the amount of data storage[14,15,20]. Hence, the distribution of databases is done according to their rate of use is an encouraging solution
This document provides an overview of nursing informatics including:
- Defining nursing informatics and its focus on integrating nursing science with multiple other fields
- The expanding roles for nurses with informatics education such as new specializations
- The importance of informatics in improving areas like communication, collaboration, and clinical decision making in patient care
- How computer systems can assist in tasks like monitoring patients, storing data, and providing alerts and diagnostics.
The document provides an introduction to health surveillance and health informatics presented by Abhishek Singh. It defines health surveillance as the systematic collection, analysis and use of health data for decision-making. Health informatics is defined as using information management and technology to organize and deliver health services. The document discusses the purposes and types of health surveillance. It also discusses key concepts and applications of health informatics including sources of health information like censuses, disease registers, and population surveys.
1) The document discusses various ways consumers use computers for health information including seeking health information online, communicating through email/online support groups, maintaining personal health records, using decision support applications, and technological support for disease management.
2) It also discusses some challenges consumers face including variable quality of online health information, security issues, and barriers to access based on age, ethnicity, socioeconomic status, education, and disabilities.
3) Nurse informaticians are well-suited to help with consumer health computing due to their expertise in patient education, cultural diversity, advocacy, and research. Special considerations in designing applications for consumers include terminology, literacy, computer literacy, accessibility, and user-centered design.
Medical informatics is the application of computers, communications, and information technology to medicine. It aims to improve patient care, medical education, and research. Key areas of medical informatics include telemedicine, knowledge management through databases and guidelines, decision support, and electronic health records. Implementation faces challenges like changing clinician behavior and raising awareness, but factors like increased technology, specialization, and costs are driving more use of informatics in healthcare.
The document discusses how health care informatics and computerized physician order entry (CPOE) systems can improve patient care by decreasing medication errors and reducing health care costs. CPOE systems work to prevent errors from incorrect data entry, transcription errors, and clinical errors. They also aim to reduce reimbursement problems from billing errors. The role of informatics specialists is to support electronic medical records and network environments while maintaining professional ethics. CPOE systems allow physicians to correctly order medications, dosages, and check for contraindications, thereby preventing errors and improving patient care.
Clinical informatics emerged in the 1960s and 1970s as the study of applying information technology to healthcare. It involves clinical care, the healthcare system, and information and communication technology. Clinical informaticians use their medical knowledge combined with informatics tools and concepts to improve healthcare processes, systems, and outcomes. Common applications include electronic health records and clinical decision support systems. While electronic health records provide benefits like reduced errors, their success depends on high quality data entry and integration across providers. Clinical informatics is still developing but shows promise to expand treatment options and improve patient care through data-driven insights.
TELEMEDICINE AND HEALTH INFORMATION TECHNOLOGIESRubashkyn
Â
The world now driving by the ICT(information and communication technologies) based services, which include innovation, several applications in industries, such as financial services, telecom and IT, media and in health care industry. The most important critical questions concerns the organizing of service innovations processes is high-tech research, service innovation and the project management research, thus there is a need for more empirical research to understand and manage ICT based service innovations. Telemedicine uses ICTs to defeat environmental barriers, and increase access to health care services. This is particularly beneficial for rural and underserved communities in developing countries, the traditionally groups suffer from lack of access to health care[1].
Telemedicine is a service in this whole process it will providing medical expertise and health services to remote, rural, and transport less area communities in primary care, and in emergency conditions with the help of telecommunications. In telemedicine are will give continuous medical monitoring for many purposes like physicians needing to early diagnosis of depression or sports persons need to monitor their condition and performance. [Baker et al. 2007; Boric-Lubecke and Lubecke 2002;Varshney 2007].
This document discusses the course Nursing Informatics. The course covers the use of information technology and data standards in nursing based on informatics principles. It deals with using clinical information systems to manage patient care and support decision making. The course objectives are to apply informatics concepts to nursing and discuss relevant issues and trends. Various topics are outlined including computers and nursing history, computer systems, issues in informatics, informatics theories, and applying informatics in different nursing practices and internationally. Students are expected to create an online nursing informatics page and do an individual or group presentation to pass the course.
The document provides an overview of biomedical informatics. It defines biomedical informatics as the interdisciplinary field that studies and pursues the effective uses of biomedical data, information, and knowledge for scientific inquiry, problem solving, and decision making, motivated by efforts to improve human health. It notes that biomedical informatics develops, studies and applies theories, methods and processes for the generation, storage, retrieval, use, and sharing of biomedical data, information, and knowledge. Biomedical informatics investigates and supports reasoning, modeling, simulation, experimentation and translation across the spectrum from molecules to populations.
The document discusses clinical informatics and how it can improve healthcare. It is presented by Iris Thiele Isip Tan, a professor and chief of the UP Medical Informatics Unit. Clinical informatics uses information and technology to enhance healthcare outcomes, improve patient care, and strengthen the clinician-patient relationship. It can assemble complete patient information, apply medical knowledge, and use decision support and other technologies to improve safety and prevent errors in healthcare delivery.
Public Health informatics, Consumer health informatics, mHealth & PHRs (Novem...Nawanan Theera-Ampornpunt
Â
Presented at the M.S. and Ph.D. Programs in Data Science for Health Care, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok, Thailand on November 11, 2019
Proposed Model for Chest Disease Prediction using Data Analyticsvivatechijri
Â
Chest diseases if not properly diagnosed in early stages can be fatal. Because of lack of skilled
knowledge or experiences of real life practitioners, many a times one chest disease is wrongly diagnosed for the
other, which leads to wrong treatment. Due to this the actual disease keeps on growing and become fatal. For
example, muscular chest pains can be treated for the heart disease or COPD is treated for Asthma. Early
prediction of chest disease is crucial but is not an easy task. Consequently, the computer based prediction system
for chest disease may play a significant role as a pre-stage detection to take proper actions with a view to recover
from it. However the choice of the proper Data Mining classification method can effectively predict the early
stage of the disease for being cured from it. In this paper, the three mostly used classification techniques such as
support vector machine (SVM), k-nearest neighbour (KNN) and artificial neural network (ANN) have been studied
with a view to evaluating them for chest disease prediction.
This document discusses health informatics and patient safety. It covers visions for patient-centered care from Judge Cartwright in 1988 and the Bristol inquiry in 2001. Health IT use in New Zealand has increased, with nearly all doctors using electronic patient records by 2009. While health IT can help when designed properly, technology alone does not ensure patient safety or effective communication - a culture of safety and strong relationships are also required. Themes around continuous learning, responsibility, and communication are highlighted. A case example describes a surgeon who unknowingly removed a patient's gallbladder twice due to a missed scan report and unreviewed records.
cognitive computing for electronic medical record selamu shirtawi
Â
This document discusses applying cognitive computing to electronic medical records (EMRs) using IBM Watson. It describes a cognitive computing system called Watson EMRA that can generate a problem-oriented summary of a patient's EMR. The summary aggregates key data like problems, medications, labs, notes, and procedures. It also identifies relationships between these data aggregates to present them in a clinically meaningful way. This type of cognitive system has the potential to reduce physicians' cognitive load when reviewing patient records and fulfilling their various information needs in clinical workflows.
This document discusses health informatics and compares it to medical informatics. Health informatics is a broader field that includes medical informatics as well as other areas like healthcare delivery, management, telemedicine, and patient education. Medical informatics focuses specifically on optimizing the storage, retrieval, and management of biomedical information. The document provides examples of areas within health informatics, such as electronic patient records, telemedicine, distance education, and how technologies in these areas can provide advantages like time savings and increased access to care.
Introduction to and History of Modern Healthcare in the US - Lecture DCMDLearning
Â
This document discusses technological advancements in healthcare delivery discussed in Lecture d. It describes how electronic health records, personal health records, and various medical technologies have positively impacted areas like accuracy, safety, integration of care, and patient access to information. Some examples provided include imaging technologies, computer-assisted surgery, clinical decision support, remote patient monitoring, and assistive technologies for rehabilitation. While costs and changes to workflows were challenges, overall the lecture emphasized that technology has allowed for incremental improvements in medical diagnosis, treatment, and management of patient data.
Health informatics: Introduction, History and general presentationDr. Khaled OUANES
Â
This document provides an overview of medical informatics as an evolving field. It discusses the history and various definitions of medical informatics. Medical informatics is defined as the systematic study that deals with acquiring, storing, retrieving, and processing medical, biological and associated data for problem solving and decision making in clinical care, health administration, research, and patient/provider education. The document also outlines key areas within medical informatics like computerized medical records, medical software, security, policy making, and biomedical computing hardware and software.
Clinical Information Systems and Electronic Health Records (October 18, 2021)Nawanan Theera-Ampornpunt
Â
This document discusses health IT in clinical settings and provides key points about IT decision making in hospitals. It outlines factors for successful IT implementation including system quality, information quality, use, and user satisfaction. Individual and organizational impacts are also discussed. Examples of important hospital IT are provided such as enterprise systems, departmental applications, and clinical IT. Clinical decision support systems are discussed as tools that can help improve clinical decision making when designed and implemented properly. Overall, the document emphasizes focusing on using health IT to improve patient care and outcomes rather than viewing technology as the end goal.
Imran Sarwar Bajwa, [2010], "Virtual Telemedicine Using Natural Language Processing", International Journal of Information Technology and Web Engineering IJITWE 5(1):43-55, January 2010
Proposed Framework For Electronic Clinical Record Information Systemijcsa
Â
This research paper is drawn from an ongoing, large-scale project of implementing Electronic Clinical Record (ECR). The overall aim in this study is to develop a deeper understanding of the socio-technical aspects of the complexities and challenges emerging from the implementation of the ECR, and in particular to study how to manage a gradual transition to digital record. We have proposed ECR conceptual mode. The end result of our research was a collection of ideas / surveys, and field work that clinical institutions and medical informatics must consider to ensure that patients and clinics do not lose long-term access to ECR and technology continually progress. Results of our study identified the need for more research in this particular area as no definitive solution to long-term access to electronic clinical records was revealed. Additionally, the research findings highlighted the fact that a few medical institutions may actually be concerned about long-term access to electronic records.
Framework Architecture for Improving Healthcare Information Systems using Age...IJMIT JOURNAL
Â
The document proposes an agent-based framework architecture for improving healthcare information systems using agent technology and case-based reasoning. The framework aims to address issues of interoperability, integration, and information sharing across different healthcare systems and platforms. Intelligent agents and case-based reasoning can help provide accurate medical information for tasks like diagnosis and treatment, and increase the speed and reliability of information exchanges between different healthcare actors and systems.
This document provides an overview of nursing informatics including:
- Defining nursing informatics and its focus on integrating nursing science with multiple other fields
- The expanding roles for nurses with informatics education such as new specializations
- The importance of informatics in improving areas like communication, collaboration, and clinical decision making in patient care
- How computer systems can assist in tasks like monitoring patients, storing data, and providing alerts and diagnostics.
The document provides an introduction to health surveillance and health informatics presented by Abhishek Singh. It defines health surveillance as the systematic collection, analysis and use of health data for decision-making. Health informatics is defined as using information management and technology to organize and deliver health services. The document discusses the purposes and types of health surveillance. It also discusses key concepts and applications of health informatics including sources of health information like censuses, disease registers, and population surveys.
1) The document discusses various ways consumers use computers for health information including seeking health information online, communicating through email/online support groups, maintaining personal health records, using decision support applications, and technological support for disease management.
2) It also discusses some challenges consumers face including variable quality of online health information, security issues, and barriers to access based on age, ethnicity, socioeconomic status, education, and disabilities.
3) Nurse informaticians are well-suited to help with consumer health computing due to their expertise in patient education, cultural diversity, advocacy, and research. Special considerations in designing applications for consumers include terminology, literacy, computer literacy, accessibility, and user-centered design.
Medical informatics is the application of computers, communications, and information technology to medicine. It aims to improve patient care, medical education, and research. Key areas of medical informatics include telemedicine, knowledge management through databases and guidelines, decision support, and electronic health records. Implementation faces challenges like changing clinician behavior and raising awareness, but factors like increased technology, specialization, and costs are driving more use of informatics in healthcare.
The document discusses how health care informatics and computerized physician order entry (CPOE) systems can improve patient care by decreasing medication errors and reducing health care costs. CPOE systems work to prevent errors from incorrect data entry, transcription errors, and clinical errors. They also aim to reduce reimbursement problems from billing errors. The role of informatics specialists is to support electronic medical records and network environments while maintaining professional ethics. CPOE systems allow physicians to correctly order medications, dosages, and check for contraindications, thereby preventing errors and improving patient care.
Clinical informatics emerged in the 1960s and 1970s as the study of applying information technology to healthcare. It involves clinical care, the healthcare system, and information and communication technology. Clinical informaticians use their medical knowledge combined with informatics tools and concepts to improve healthcare processes, systems, and outcomes. Common applications include electronic health records and clinical decision support systems. While electronic health records provide benefits like reduced errors, their success depends on high quality data entry and integration across providers. Clinical informatics is still developing but shows promise to expand treatment options and improve patient care through data-driven insights.
TELEMEDICINE AND HEALTH INFORMATION TECHNOLOGIESRubashkyn
Â
The world now driving by the ICT(information and communication technologies) based services, which include innovation, several applications in industries, such as financial services, telecom and IT, media and in health care industry. The most important critical questions concerns the organizing of service innovations processes is high-tech research, service innovation and the project management research, thus there is a need for more empirical research to understand and manage ICT based service innovations. Telemedicine uses ICTs to defeat environmental barriers, and increase access to health care services. This is particularly beneficial for rural and underserved communities in developing countries, the traditionally groups suffer from lack of access to health care[1].
Telemedicine is a service in this whole process it will providing medical expertise and health services to remote, rural, and transport less area communities in primary care, and in emergency conditions with the help of telecommunications. In telemedicine are will give continuous medical monitoring for many purposes like physicians needing to early diagnosis of depression or sports persons need to monitor their condition and performance. [Baker et al. 2007; Boric-Lubecke and Lubecke 2002;Varshney 2007].
This document discusses the course Nursing Informatics. The course covers the use of information technology and data standards in nursing based on informatics principles. It deals with using clinical information systems to manage patient care and support decision making. The course objectives are to apply informatics concepts to nursing and discuss relevant issues and trends. Various topics are outlined including computers and nursing history, computer systems, issues in informatics, informatics theories, and applying informatics in different nursing practices and internationally. Students are expected to create an online nursing informatics page and do an individual or group presentation to pass the course.
The document provides an overview of biomedical informatics. It defines biomedical informatics as the interdisciplinary field that studies and pursues the effective uses of biomedical data, information, and knowledge for scientific inquiry, problem solving, and decision making, motivated by efforts to improve human health. It notes that biomedical informatics develops, studies and applies theories, methods and processes for the generation, storage, retrieval, use, and sharing of biomedical data, information, and knowledge. Biomedical informatics investigates and supports reasoning, modeling, simulation, experimentation and translation across the spectrum from molecules to populations.
The document discusses clinical informatics and how it can improve healthcare. It is presented by Iris Thiele Isip Tan, a professor and chief of the UP Medical Informatics Unit. Clinical informatics uses information and technology to enhance healthcare outcomes, improve patient care, and strengthen the clinician-patient relationship. It can assemble complete patient information, apply medical knowledge, and use decision support and other technologies to improve safety and prevent errors in healthcare delivery.
Public Health informatics, Consumer health informatics, mHealth & PHRs (Novem...Nawanan Theera-Ampornpunt
Â
Presented at the M.S. and Ph.D. Programs in Data Science for Health Care, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok, Thailand on November 11, 2019
Proposed Model for Chest Disease Prediction using Data Analyticsvivatechijri
Â
Chest diseases if not properly diagnosed in early stages can be fatal. Because of lack of skilled
knowledge or experiences of real life practitioners, many a times one chest disease is wrongly diagnosed for the
other, which leads to wrong treatment. Due to this the actual disease keeps on growing and become fatal. For
example, muscular chest pains can be treated for the heart disease or COPD is treated for Asthma. Early
prediction of chest disease is crucial but is not an easy task. Consequently, the computer based prediction system
for chest disease may play a significant role as a pre-stage detection to take proper actions with a view to recover
from it. However the choice of the proper Data Mining classification method can effectively predict the early
stage of the disease for being cured from it. In this paper, the three mostly used classification techniques such as
support vector machine (SVM), k-nearest neighbour (KNN) and artificial neural network (ANN) have been studied
with a view to evaluating them for chest disease prediction.
This document discusses health informatics and patient safety. It covers visions for patient-centered care from Judge Cartwright in 1988 and the Bristol inquiry in 2001. Health IT use in New Zealand has increased, with nearly all doctors using electronic patient records by 2009. While health IT can help when designed properly, technology alone does not ensure patient safety or effective communication - a culture of safety and strong relationships are also required. Themes around continuous learning, responsibility, and communication are highlighted. A case example describes a surgeon who unknowingly removed a patient's gallbladder twice due to a missed scan report and unreviewed records.
cognitive computing for electronic medical record selamu shirtawi
Â
This document discusses applying cognitive computing to electronic medical records (EMRs) using IBM Watson. It describes a cognitive computing system called Watson EMRA that can generate a problem-oriented summary of a patient's EMR. The summary aggregates key data like problems, medications, labs, notes, and procedures. It also identifies relationships between these data aggregates to present them in a clinically meaningful way. This type of cognitive system has the potential to reduce physicians' cognitive load when reviewing patient records and fulfilling their various information needs in clinical workflows.
This document discusses health informatics and compares it to medical informatics. Health informatics is a broader field that includes medical informatics as well as other areas like healthcare delivery, management, telemedicine, and patient education. Medical informatics focuses specifically on optimizing the storage, retrieval, and management of biomedical information. The document provides examples of areas within health informatics, such as electronic patient records, telemedicine, distance education, and how technologies in these areas can provide advantages like time savings and increased access to care.
Introduction to and History of Modern Healthcare in the US - Lecture DCMDLearning
Â
This document discusses technological advancements in healthcare delivery discussed in Lecture d. It describes how electronic health records, personal health records, and various medical technologies have positively impacted areas like accuracy, safety, integration of care, and patient access to information. Some examples provided include imaging technologies, computer-assisted surgery, clinical decision support, remote patient monitoring, and assistive technologies for rehabilitation. While costs and changes to workflows were challenges, overall the lecture emphasized that technology has allowed for incremental improvements in medical diagnosis, treatment, and management of patient data.
Health informatics: Introduction, History and general presentationDr. Khaled OUANES
Â
This document provides an overview of medical informatics as an evolving field. It discusses the history and various definitions of medical informatics. Medical informatics is defined as the systematic study that deals with acquiring, storing, retrieving, and processing medical, biological and associated data for problem solving and decision making in clinical care, health administration, research, and patient/provider education. The document also outlines key areas within medical informatics like computerized medical records, medical software, security, policy making, and biomedical computing hardware and software.
Clinical Information Systems and Electronic Health Records (October 18, 2021)Nawanan Theera-Ampornpunt
Â
This document discusses health IT in clinical settings and provides key points about IT decision making in hospitals. It outlines factors for successful IT implementation including system quality, information quality, use, and user satisfaction. Individual and organizational impacts are also discussed. Examples of important hospital IT are provided such as enterprise systems, departmental applications, and clinical IT. Clinical decision support systems are discussed as tools that can help improve clinical decision making when designed and implemented properly. Overall, the document emphasizes focusing on using health IT to improve patient care and outcomes rather than viewing technology as the end goal.
Imran Sarwar Bajwa, [2010], "Virtual Telemedicine Using Natural Language Processing", International Journal of Information Technology and Web Engineering IJITWE 5(1):43-55, January 2010
Proposed Framework For Electronic Clinical Record Information Systemijcsa
Â
This research paper is drawn from an ongoing, large-scale project of implementing Electronic Clinical Record (ECR). The overall aim in this study is to develop a deeper understanding of the socio-technical aspects of the complexities and challenges emerging from the implementation of the ECR, and in particular to study how to manage a gradual transition to digital record. We have proposed ECR conceptual mode. The end result of our research was a collection of ideas / surveys, and field work that clinical institutions and medical informatics must consider to ensure that patients and clinics do not lose long-term access to ECR and technology continually progress. Results of our study identified the need for more research in this particular area as no definitive solution to long-term access to electronic clinical records was revealed. Additionally, the research findings highlighted the fact that a few medical institutions may actually be concerned about long-term access to electronic records.
Framework Architecture for Improving Healthcare Information Systems using Age...IJMIT JOURNAL
Â
The document proposes an agent-based framework architecture for improving healthcare information systems using agent technology and case-based reasoning. The framework aims to address issues of interoperability, integration, and information sharing across different healthcare systems and platforms. Intelligent agents and case-based reasoning can help provide accurate medical information for tasks like diagnosis and treatment, and increase the speed and reliability of information exchanges between different healthcare actors and systems.
The document proposes an agent-based framework architecture using intelligent agents and case-based reasoning to improve integration and interoperability among heterogeneous healthcare information systems. Intelligent agents would play a critical role in providing correct diagnostic and treatment information to medical staff. Case-based reasoning would be used to generate advice for healthcare problems by analyzing solutions to previous similar problems. A preliminary simulation demonstrated the feasibility of using an agent development framework and case-based reasoning to address issues like fragmented patient records and inefficient information sharing across different healthcare systems.
CONCEPTUAL MODEL FOR ELECTRONIC CLINICAL RECORD INFORMATION SYSTEMijistjournal
Â
This study is drawn from an ongoing, large-scale project of implementing Electronic Clinical Record (ECR). The overall aim in this study is to develop a deeper understanding of the socio-technical aspects of the complexities and challenges emerging from the implementation of the ECR, and in particular to study how to manage a gradual transition to digital record. We have proposed ECR conceptual model. The end result of our research was a collection of ideas / surveys, and field work that clinical institutions and medical informatics must consider to ensure that patients and clinics do not lose long-term access to ECR and technology continually progress. Results of our study identified the need for more research in this particular area as no definitive solution to long-term access to electronic clinical records was revealed. Additionally, the research findings highlighted the fact that a few medical institutions may actually be concerned about long-term access to electronic records.
CONCEPTUAL MODEL FOR ELECTRONIC CLINICAL RECORD INFORMATION SYSTEMijistjournal
Â
This study is drawn from an ongoing, large-scale project of implementing Electronic Clinical Record (ECR). The overall aim in this study is to develop a deeper understanding of the socio-technical aspects of the complexities and challenges emerging from the implementation of the ECR, and in particular to study how to manage a gradual transition to digital record. We have proposed ECR conceptual model. The end result of our research was a collection of ideas / surveys, and field work that clinical institutions and medical informatics must consider to ensure that patients and clinics do not lose long-term access to ECR and technology continually progress. Results of our study identified the need for more research in this particular area as no definitive solution to long-term access to electronic clinical records was revealed. Additionally, the research findings highlighted the fact that a few medical institutions may actually be concerned about long-term access to electronic records.
A framework for secure healthcare systems based on big data analytics in mobi...ijasa
Â
In this paper we introduce a framework for Healthcare Information Systems (HISs) based on big data
analytics in mobile cloud computing environments. This framework provides a high level of integration,
interoperability, availability and sharing of healthcare data among healthcare providers, patients, and
practitioners. Electronic Medical Records (EMRs) of patients dispersed among different Care Delivery
Organizations (CDOs) are integrated and stored in the Cloud storage area, this creates an Electronic
Health Records (EHRs) for each patient. Mobile Cloud allows fast Internet access and provision of EHRs
from anywhere and at any time via different platforms. Due to the massive size of healthcare data, the
exponential increase in the speed in which this data is generated and the complexity of healthcare data
type, the proposed framework employs big data analytics to find useful insights that help practitioners take
critical decisions in the right time. In addition, our proposed framework applies a set of security
constraints and access control that guarantee integrity, confidentiality, and privacy of medical information.
We believe that the proposed framework paves the way for a new generation of lower cost, more efficient
healthcare systems.
E-Health is alluded to as utilizing of information and communication technologies (ICT) in restorative field to control treatment of patients, research, and wellbeing training and checking of general wellbeing. The reason for this paper is thusly to investigate an institutionalized system for E-Health challenges confronted
by e-wellbeing A rundown of both e-wellbeing difficulties are given and a proposed structure is likewise accommodated E-Health and could give direction in the execution of e-wellbeing To understand the motivation behind the paper, an inductive substance examination procedure was taken after. The
fundamental outcomes were that in spite of the fact that the difficulties exceeds the advantages in the gave records, there is still trust that through appropriate ICT arrangements the advantages of e-wellbeing can develop all the more quickly. This can prompt to enhanced e-wellbeing administration conveyance and nationals in nations can all profit by this.
Modern Era of Medical Field : E-HealthFull Text ijbbjournal
Â
E-Health is alluded to as utilizing of information and communication technologies (ICT) in restorative field
to control treatment of patients, research, and wellbeing training and checking of general wellbeing. The
reason for this paper is thusly to investigate an institutionalized system for E-Health challenges confronted
by e-wellbeing A rundown of both e-wellbeing difficulties are given and a proposed structure is likewise
accommodated E-Health and could give direction in the execution of e-wellbeing To understand the
motivation behind the paper, an inductive substance examination procedure was taken after. The
fundamental outcomes were that in spite of the fact that the difficulties exceeds the advantages in the gave
records, there is still trust that through appropriate ICT arrangements the advantages of e-wellbeing can
develop all the more quickly. This can prompt to enhanced e-wellbeing administration conveyance and
nationals in nations can all profit by this
Framework for Data Warehousing and Mining Clinical Records of Patients: A ReviewBRNSSPublicationHubI
Â
This document discusses a framework for data warehousing and mining clinical records of patients. It begins with an abstract that describes how a clinical data warehouse can provide access to clinical data for healthcare providers and support areas like research and management. The rest of the document reviews the background and need for integrating disparate clinical data sources, describes challenges in current fragmented systems, and discusses the significance of developing a clinical data warehousing and mining framework to organize and extract medical records from different systems.
Lecture 1_ Introduction to Health Informatics.pptxJosephmwanika
Â
The document discusses health informatics and related topics. It defines health informatics as the practice of acquiring, studying, and managing health data and applying medical concepts using health information technology (HIT) systems to help clinicians provide better healthcare. It also discusses biomedical informatics, bioinformatics, personal health records, telehealth, telemedicine, and provides examples of applications of health informatics including using artificial intelligence to predict cancer progression and smart devices to monitor patients. The importance of health informatics is maintaining electronic patient records and reducing costs by lessening medical errors.
Advances in Health informatics and telemedicine are providing greater access....write22
Â
1. Advances in health informatics and telemedicine can provide greater access to healthcare resources for those living in rural areas with fewer medical practitioners and services.
2. These technologies allow for electronic health records, remote monitoring, and real-time interactions like teleconsultations that reduce the need to travel long distances for care.
3. While these approaches have benefits, they also face challenges in technology setup and costs, as well as potential issues around privacy, guidelines, and resistance to change.
Disease detection for multilabel big dataset using MLAM, Naive Bayes, Adaboos...IRJET Journal
Â
The document proposes a framework to efficiently assign disease labels to patient records in large medical datasets by considering correlations between diseases. It extracts features from both structured chart data and unstructured note data, encodes the features using bag-of-words, and proposes an algorithm that classifies disease labels using a sparsity-based model to capture relationships between diseases represented as a graph. The algorithm is evaluated on a large real-world medical database using Hadoop MapReduce to reduce time complexity, and disease labels are predicted using Naive Bayes and AdaBoost classification algorithms.
mHealth involves using mobile devices and wireless technologies in healthcare, including delivering health services and information via mobile phones. It has the potential to improve access to care, especially in remote areas, by connecting healthcare workers and allowing remote monitoring of patients. However, concerns exist around privacy, data protection, equity of access, and how mHealth might change patient-provider relationships and healthcare delivery models. Effective implementation requires addressing issues like coordination of projects, integration with existing healthcare systems, and impacts on healthcare workers and their workloads.
International Journal of Computational Engineering Research(IJCER)ijceronline
Â
International Journal of Computational Engineering Research(IJCER) is an intentional online Journal in English monthly publishing journal. This Journal publish original research work that contributes significantly to further the scientific knowledge in engineering and Technology.
Implementation of Remote Health Monitoring in Medical Rural Clinics for Web T...Eswar Publications
Â
The problem with limited numbers of physicians, nurses, and other healthcare providers is expected to exacerbate. Health
care must be as efficient as possible. This situation provides an opportunity for the application of telehealth clinics. It is time for organizations providing health care to objectively consider telehealth clinics. Information and communication technologies (ICTs) have great potential to address some of the challenges faced by both developed and developing countries in providing accessible, cost-effective, high-quality health care services. Telemedical clinics use ICTs to overcome geographical barriers, and increase access to healthcare services. This is particularly beneficial for rural and underserved communities in developing countries – groups that traditionally suffer from lack of access to health care. In this work we propose an equipped system with new technology to provide wide range of services in Telemedical clinics which facilitates the provision of medical aids from a distance. It is an effective solution for providing specialty healthcare in the form of improved access and reduced cost to the rural patients and the reduced professional isolation of the rural doctors. Telemedical clinics can enable ordinary doctors to perform extra-ordinary tasks.
This document summarizes a research paper on developing a cloud-based health prediction system. The system allows users to enter their health issues and details like weight and height online. It then provides an accurate health prediction by matching the user's data to an analysis database. The cloud-based system is designed to be user-friendly and accessible from anywhere at any time. It aims to help users identify potential health problems early without visiting a doctor. The system architecture uses HTML, CSS, JavaScript, PHP and a MySQL database. It flows user data through registration, selecting health details, and logout for security.
1. The document discusses the advantages and disadvantages of implementing an electronic health record (EHR) system to replace a paper-based system.
2. A key disadvantage is the high cost of implementation, with the cost of Alberta's new clinical information system estimated at $1.6 billion over 10 years.
3. Another disadvantage is a lack of interoperability between existing EHR systems, which prevents patient information from being shared and understood across health settings.
IRJET-Cloud based Patient Referral System with RFID Based Clinical Informatio...IRJET Journal
Â
This document summarizes a proposed cloud-based patient referral system with RFID-based clinical information retrieval for emergency cases. The system allows patients to directly communicate with remotely located healthcare professionals to schedule appointments, saving both time and money. It also integrates RFID technology to provide doctors with unconscious or unaccompanied patients' accurate medical histories in emergency situations, making treatment more efficient and reducing risks. The system architecture includes an Android app for patients and doctors to register and access services, a cloud database to store medical records, RFID tags and readers to retrieve records during emergencies, and other components like Arduino and WiFi modules to process and transmit RFID data. The goal is to improve healthcare access, efficiency and
Similar to Web based database management to support telemedicine system (20)
Your One-Stop Shop for Python Success: Top 10 US Python Development Providersakankshawande
Â
Simplify your search for a reliable Python development partner! This list presents the top 10 trusted US providers offering comprehensive Python development services, ensuring your project's success from conception to completion.
5th LF Energy Power Grid Model Meet-up SlidesDanBrown980551
Â
5th Power Grid Model Meet-up
It is with great pleasure that we extend to you an invitation to the 5th Power Grid Model Meet-up, scheduled for 6th June 2024. This event will adopt a hybrid format, allowing participants to join us either through an online Mircosoft Teams session or in person at TU/e located at Den Dolech 2, Eindhoven, Netherlands. The meet-up will be hosted by Eindhoven University of Technology (TU/e), a research university specializing in engineering science & technology.
Power Grid Model
The global energy transition is placing new and unprecedented demands on Distribution System Operators (DSOs). Alongside upgrades to grid capacity, processes such as digitization, capacity optimization, and congestion management are becoming vital for delivering reliable services.
Power Grid Model is an open source project from Linux Foundation Energy and provides a calculation engine that is increasingly essential for DSOs. It offers a standards-based foundation enabling real-time power systems analysis, simulations of electrical power grids, and sophisticated what-if analysis. In addition, it enables in-depth studies and analysis of the electrical power grid’s behavior and performance. This comprehensive model incorporates essential factors such as power generation capacity, electrical losses, voltage levels, power flows, and system stability.
Power Grid Model is currently being applied in a wide variety of use cases, including grid planning, expansion, reliability, and congestion studies. It can also help in analyzing the impact of renewable energy integration, assessing the effects of disturbances or faults, and developing strategies for grid control and optimization.
What to expect
For the upcoming meetup we are organizing, we have an exciting lineup of activities planned:
-Insightful presentations covering two practical applications of the Power Grid Model.
-An update on the latest advancements in Power Grid -Model technology during the first and second quarters of 2024.
-An interactive brainstorming session to discuss and propose new feature requests.
-An opportunity to connect with fellow Power Grid Model enthusiasts and users.
Monitoring and Managing Anomaly Detection on OpenShift.pdfTosin Akinosho
Â
Monitoring and Managing Anomaly Detection on OpenShift
Overview
Dive into the world of anomaly detection on edge devices with our comprehensive hands-on tutorial. This SlideShare presentation will guide you through the entire process, from data collection and model training to edge deployment and real-time monitoring. Perfect for those looking to implement robust anomaly detection systems on resource-constrained IoT/edge devices.
Key Topics Covered
1. Introduction to Anomaly Detection
- Understand the fundamentals of anomaly detection and its importance in identifying unusual behavior or failures in systems.
2. Understanding Edge (IoT)
- Learn about edge computing and IoT, and how they enable real-time data processing and decision-making at the source.
3. What is ArgoCD?
- Discover ArgoCD, a declarative, GitOps continuous delivery tool for Kubernetes, and its role in deploying applications on edge devices.
4. Deployment Using ArgoCD for Edge Devices
- Step-by-step guide on deploying anomaly detection models on edge devices using ArgoCD.
5. Introduction to Apache Kafka and S3
- Explore Apache Kafka for real-time data streaming and Amazon S3 for scalable storage solutions.
6. Viewing Kafka Messages in the Data Lake
- Learn how to view and analyze Kafka messages stored in a data lake for better insights.
7. What is Prometheus?
- Get to know Prometheus, an open-source monitoring and alerting toolkit, and its application in monitoring edge devices.
8. Monitoring Application Metrics with Prometheus
- Detailed instructions on setting up Prometheus to monitor the performance and health of your anomaly detection system.
9. What is Camel K?
- Introduction to Camel K, a lightweight integration framework built on Apache Camel, designed for Kubernetes.
10. Configuring Camel K Integrations for Data Pipelines
- Learn how to configure Camel K for seamless data pipeline integrations in your anomaly detection workflow.
11. What is a Jupyter Notebook?
- Overview of Jupyter Notebooks, an open-source web application for creating and sharing documents with live code, equations, visualizations, and narrative text.
12. Jupyter Notebooks with Code Examples
- Hands-on examples and code snippets in Jupyter Notebooks to help you implement and test anomaly detection models.
Main news related to the CCS TSI 2023 (2023/1695)Jakub Marek
Â
An English 🇬🇧 translation of a presentation to the speech I gave about the main changes brought by CCS TSI 2023 at the biggest Czech conference on Communications and signalling systems on Railways, which was held in Clarion Hotel Olomouc from 7th to 9th November 2023 (konferenceszt.cz). Attended by around 500 participants and 200 on-line followers.
The original Czech 🇨🇿 version of the presentation can be found here: https://www.slideshare.net/slideshow/hlavni-novinky-souvisejici-s-ccs-tsi-2023-2023-1695/269688092 .
The videorecording (in Czech) from the presentation is available here: https://youtu.be/WzjJWm4IyPk?si=SImb06tuXGb30BEH .
Unlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdfMalak Abu Hammad
Â
Discover how MongoDB Atlas and vector search technology can revolutionize your application's search capabilities. This comprehensive presentation covers:
* What is Vector Search?
* Importance and benefits of vector search
* Practical use cases across various industries
* Step-by-step implementation guide
* Live demos with code snippets
* Enhancing LLM capabilities with vector search
* Best practices and optimization strategies
Perfect for developers, AI enthusiasts, and tech leaders. Learn how to leverage MongoDB Atlas to deliver highly relevant, context-aware search results, transforming your data retrieval process. Stay ahead in tech innovation and maximize the potential of your applications.
#MongoDB #VectorSearch #AI #SemanticSearch #TechInnovation #DataScience #LLM #MachineLearning #SearchTechnology
Taking AI to the Next Level in Manufacturing.pdfssuserfac0301
Â
Read Taking AI to the Next Level in Manufacturing to gain insights on AI adoption in the manufacturing industry, such as:
1. How quickly AI is being implemented in manufacturing.
2. Which barriers stand in the way of AI adoption.
3. How data quality and governance form the backbone of AI.
4. Organizational processes and structures that may inhibit effective AI adoption.
6. Ideas and approaches to help build your organization's AI strategy.
Dive into the realm of operating systems (OS) with Pravash Chandra Das, a seasoned Digital Forensic Analyst, as your guide. 🚀 This comprehensive presentation illuminates the core concepts, types, and evolution of OS, essential for understanding modern computing landscapes.
Beginning with the foundational definition, Das clarifies the pivotal role of OS as system software orchestrating hardware resources, software applications, and user interactions. Through succinct descriptions, he delineates the diverse types of OS, from single-user, single-task environments like early MS-DOS iterations, to multi-user, multi-tasking systems exemplified by modern Linux distributions.
Crucial components like the kernel and shell are dissected, highlighting their indispensable functions in resource management and user interface interaction. Das elucidates how the kernel acts as the central nervous system, orchestrating process scheduling, memory allocation, and device management. Meanwhile, the shell serves as the gateway for user commands, bridging the gap between human input and machine execution. đź’»
The narrative then shifts to a captivating exploration of prominent desktop OSs, Windows, macOS, and Linux. Windows, with its globally ubiquitous presence and user-friendly interface, emerges as a cornerstone in personal computing history. macOS, lauded for its sleek design and seamless integration with Apple's ecosystem, stands as a beacon of stability and creativity. Linux, an open-source marvel, offers unparalleled flexibility and security, revolutionizing the computing landscape. 🖥️
Moving to the realm of mobile devices, Das unravels the dominance of Android and iOS. Android's open-source ethos fosters a vibrant ecosystem of customization and innovation, while iOS boasts a seamless user experience and robust security infrastructure. Meanwhile, discontinued platforms like Symbian and Palm OS evoke nostalgia for their pioneering roles in the smartphone revolution.
The journey concludes with a reflection on the ever-evolving landscape of OS, underscored by the emergence of real-time operating systems (RTOS) and the persistent quest for innovation and efficiency. As technology continues to shape our world, understanding the foundations and evolution of operating systems remains paramount. Join Pravash Chandra Das on this illuminating journey through the heart of computing. 🌟
Driving Business Innovation: Latest Generative AI Advancements & Success StorySafe Software
Â
Are you ready to revolutionize how you handle data? Join us for a webinar where we’ll bring you up to speed with the latest advancements in Generative AI technology and discover how leveraging FME with tools from giants like Google Gemini, Amazon, and Microsoft OpenAI can supercharge your workflow efficiency.
During the hour, we’ll take you through:
Guest Speaker Segment with Hannah Barrington: Dive into the world of dynamic real estate marketing with Hannah, the Marketing Manager at Workspace Group. Hear firsthand how their team generates engaging descriptions for thousands of office units by integrating diverse data sources—from PDF floorplans to web pages—using FME transformers, like OpenAIVisionConnector and AnthropicVisionConnector. This use case will show you how GenAI can streamline content creation for marketing across the board.
Ollama Use Case: Learn how Scenario Specialist Dmitri Bagh has utilized Ollama within FME to input data, create custom models, and enhance security protocols. This segment will include demos to illustrate the full capabilities of FME in AI-driven processes.
Custom AI Models: Discover how to leverage FME to build personalized AI models using your data. Whether it’s populating a model with local data for added security or integrating public AI tools, find out how FME facilitates a versatile and secure approach to AI.
We’ll wrap up with a live Q&A session where you can engage with our experts on your specific use cases, and learn more about optimizing your data workflows with AI.
This webinar is ideal for professionals seeking to harness the power of AI within their data management systems while ensuring high levels of customization and security. Whether you're a novice or an expert, gain actionable insights and strategies to elevate your data processes. Join us to see how FME and AI can revolutionize how you work with data!
Ivanti’s Patch Tuesday breakdown goes beyond patching your applications and brings you the intelligence and guidance needed to prioritize where to focus your attention first. Catch early analysis on our Ivanti blog, then join industry expert Chris Goettl for the Patch Tuesday Webinar Event. There we’ll do a deep dive into each of the bulletins and give guidance on the risks associated with the newly-identified vulnerabilities.
Ocean lotus Threat actors project by John Sitima 2024 (1).pptxSitimaJohn
Â
Ocean Lotus cyber threat actors represent a sophisticated, persistent, and politically motivated group that poses a significant risk to organizations and individuals in the Southeast Asian region. Their continuous evolution and adaptability underscore the need for robust cybersecurity measures and international cooperation to identify and mitigate the threats posed by such advanced persistent threat groups.
Have you ever been confused by the myriad of choices offered by AWS for hosting a website or an API?
Lambda, Elastic Beanstalk, Lightsail, Amplify, S3 (and more!) can each host websites + APIs. But which one should we choose?
Which one is cheapest? Which one is fastest? Which one will scale to meet our needs?
Join me in this session as we dive into each AWS hosting service to determine which one is best for your scenario and explain why!
In the rapidly evolving landscape of technologies, XML continues to play a vital role in structuring, storing, and transporting data across diverse systems. The recent advancements in artificial intelligence (AI) present new methodologies for enhancing XML development workflows, introducing efficiency, automation, and intelligent capabilities. This presentation will outline the scope and perspective of utilizing AI in XML development. The potential benefits and the possible pitfalls will be highlighted, providing a balanced view of the subject.
We will explore the capabilities of AI in understanding XML markup languages and autonomously creating structured XML content. Additionally, we will examine the capacity of AI to enrich plain text with appropriate XML markup. Practical examples and methodological guidelines will be provided to elucidate how AI can be effectively prompted to interpret and generate accurate XML markup.
Further emphasis will be placed on the role of AI in developing XSLT, or schemas such as XSD and Schematron. We will address the techniques and strategies adopted to create prompts for generating code, explaining code, or refactoring the code, and the results achieved.
The discussion will extend to how AI can be used to transform XML content. In particular, the focus will be on the use of AI XPath extension functions in XSLT, Schematron, Schematron Quick Fixes, or for XML content refactoring.
The presentation aims to deliver a comprehensive overview of AI usage in XML development, providing attendees with the necessary knowledge to make informed decisions. Whether you’re at the early stages of adopting AI or considering integrating it in advanced XML development, this presentation will cover all levels of expertise.
By highlighting the potential advantages and challenges of integrating AI with XML development tools and languages, the presentation seeks to inspire thoughtful conversation around the future of XML development. We’ll not only delve into the technical aspects of AI-powered XML development but also discuss practical implications and possible future directions.
leewayhertz.com-AI in predictive maintenance Use cases technologies benefits ...alexjohnson7307
Â
Predictive maintenance is a proactive approach that anticipates equipment failures before they happen. At the forefront of this innovative strategy is Artificial Intelligence (AI), which brings unprecedented precision and efficiency. AI in predictive maintenance is transforming industries by reducing downtime, minimizing costs, and enhancing productivity.
leewayhertz.com-AI in predictive maintenance Use cases technologies benefits ...
Â
Web based database management to support telemedicine system
1. International Journal of Advanced Information Technology (IJAIT) Vol. 4, No. 1, February 2014
DOI : 10.5121/ijait.2013.4101 1
WEB-BASED DATABASE MANAGEMENT TO
SUPPORT TELEMEDICINE SYSTEM
Hafez Fouad
Microelectronics Dept., Electronics Research Institute, Cairo, Egypt
ABSTRACT
The transfer of the medical care services to the patient, rather than the transport of the patient to the
medical services providers is aim of the project. This is achieved by using web-based applications including
Modern Medical Informatics Services which is easier, faster and less expensive. The required system
implements the suitable informatics and electronics solutions efficiently for the Tele-medicine care. We
proposed an approach to manage different multimedia medical databases in the telemedicine system. In
order to be efficiently and effectively manage, search, and display database information, we define an
information package for both of doctor and patient as a concise data set of their medical information from
each visit. The methodology for accessing various types of medical records will be provided, also we will
design two web-based interfaces, high-quality data and display for many medical service purposes.
KEYWORDS
Telemedicine, Medical database, Teleconferencing, Teleconsultation, Telediagnos is, Medical Informatics,
web-based medicals applications.
1. INTRODUCTION
There are shortages of medical resources in rural areas or geographically isolated regions, so many
physicians may be reluctant to serve in these areas. Therefore, people who live there will receive
lower medical care than those who live in urban areas. There is an important need to develop a
telemedicine system to improve the quality of medical services there and provide more
educational opportunities to the physicians in these areas [1]–[4].Telemedicine can be defined as
the providing of medical services over a distance. The Archiving and Communication System
(PACS) will be used in the telemedicine process as this service requires patient history, medical
images, and related information. By using PACS [5]–[11], we can find that the integrated
telemedicine system consists of the following five subsystems:
1) Acquisition subsystem;
2) Viewing subsystem;
3) Teleconferencing subsystem;
4) Communication subsystem;
5) Database management subsystem.
The first subsystem is the acquisition subsystem which collects multimedia information [12] then
converts it to a standard format (e.g., DICOM 3.0 [13]). The second one isthe viewing subsystem
which displays and manipulates the images and other medical information [14]–[15]. The third
one is the teleconferencing subsystem which allows face-to-face interactive conference between
2. International Journal of Advanced Information Technology (IJAIT) Vol. 4, No. 1, February 2014
2
physicians in rural areas and medical centers [16]–[18],this subsystem is not included in a PACS.
The forth one is the communication subsystem which includes the connectivity method; local area
networks (LAN’s)and a wide area network (WAN) to transmit and receive data[19]–[21].The
patient medical record consists of the patient complaint, history of illness, results of physical
examination, laboratory tests, and diagnostic images. The medical information may be of the
following types: text, voice, image [e.g., x-ray, computed tomography (CT), or magnetic
resonance imaging (MRI)], and dynamic video (e.g., videoesophagogram and endoscopy) [22]–
[24]. Thus, it is essential to design a medical information database for managing a huge amount of
heterogeneous data. In some studies [14],[25]–[27] However, this approach may complicate
archiving operations and introduce an inconsistency problem while concurrently accessing the
image data [28]–[30]. This management approach may make it difficult to access the videotapes
and share themsimultaneously. Moreover, the integration of video with text and images in a
telemedicine system is a problem.
To solve these problems, a data management methodology is proposed which is the fifth
subsystem, by which medical information can be organizedbased on the patient’s complaint as
well as the medical history. This will supporta unified interface for manipulating and accessing the
different types of all medical information mentioned above. The management of medical
databases and the user interface has been implemented as major components of a telemedicine
system through A in Medical. Com web-Portal.
2. SYSTEM ANALYSIS AND DESIGN
2.1. Telemedicine System Service
In this paper, we have developed a telemedicine system that supports teleconsultation, telediagnos
is, and tele-education. In teleconsultation, rural physicians referred their patients to the medical
specialists at a medical center who provide second opinion for them. The patient’s medical records
will be shared between the rural physicians and the specialists; they will discuss the symptoms of
the patient’s conditions interactively. The patient’s final diagnosis is reached following discussion
between the two physicians.
In teleconsultation, we need a synchronous two-way videoconferencing system as well as a
document-sharing mechanism to allow rural physicians to send their patient’s medical information
to specialists and engage in face-to-face conversation. In telediagnosis, it is similar to
teleconsultation, but the specialist makes a diagnosis based on the received information. The
specialist makes the diagnosis and then forwards the diagnosis report to the rural physician. The
major difference between them is that the telediagnosis requires high-quality data and images to
achieve an accurate diagnosis, while the teleconsultation requires a synchronously interactive
conference environment. Telediagnosis can be performed asynchronously. In tele-education, a
rural physician playing a student role obtains advanced medical expertise from the specialists.
There are two ways to deliver tele-education to rural physicians. First, knowledge may be
delivered in a face-to-face manner through teleconferencing between the rural physician and the
specialist. So, a real-time videoconferencing system capability is required for interactive
communication. Second, the knowledge may be put in medical teaching materials which can be
organized and converted to a digital multimedia textbook presented on the World Wide Web
(WWW). A network discussion panel may also be created for exchanging ideas and discussing
problems among the rural physician and the specialist. Rural physicians can access these materials
and educate themselves via the Internet. So, an authoring tool for compiling the medical teaching
materials and a friendly userinterface for browsing and discussing the multimedia textbook are
required.
3. International Journal of Advanced Information Technology (IJAIT) Vol. 4, No. 1, February 2014
3
In order to meet the requirements of teleconsultation, telediagnosis, and tele-education
simultaneously, patient medical records and the associated images must be organized in such a
way that a physician can easily access the database based either on a patient’s clinical history or
on particular cases (clinical problems). This requires that the database must meet different
purposes by providing both patient-oriented data folders and problem-oriented data folders. A
patient-oriented data folder is used to store all the medical records of a single patient; a problem-
oriented data folder is used to store all the medical records of one specific case.
2.2. Conceptual Databases Models
We know that the physician makes a diagnosis and treatment plan in the clinical practice not only
based on the patient’s current situation, but also on a review of the patient’s history and references
in similar disease symptoms. The current traditional medical databases are constructed according
to the type of material in the records. These records may be laboratory data, consultant comments,
physicians’ notes, and diagnostic medical images from different sources and each of them were
managed in separate files. Although this management method is relatively easy to maintain, it is
difficult to trace the history of particular problem. To resolve this difficulty, we defined a database
as a concise data set containing all of the medical diagnostic information of the patient. Besides,
the database package can manage and save any change of status or new information that emerges
from the subjective description, objective description, assessment, and plan; these derivations are
based on subjective, objective, assessment, and plan (SOAP) medical record methodology [30].
The subjective description (S) refers to the description of a patient’s chief complaint and the
history of the disease problem. It is interpreted from the patient’s point of view, and in this study,
includes symptom code, duration, location, severity, description, and chief complaint. The
objective description (O) records the results of all measurements during the current visit and
factual plan results as noted by the physician during the previous visit concerning the same
problem. In this part, physical examination results, laboratory data, and diagnostic plan
conclusions are summarized in the fields of item, location, finding, sign-code, and description.
The assessment information, part A, records the physician’s diagnosis and a description of the
disease problem based on the information in part S and part O It is expressed with the problem ID
and an assessment description. The plan information, part Prefers to the diagnostic and therapeutic
plans made by the physician specifically addressing the patient’s problem.
2.3. Database Implementation
It is noteworthy that, as in Fig. 1, part of the medical record is a form of multimedia. An important
point in system design is how to build a medical information database system to manage
heterogeneous data. Although the relational database provides a set of powerful tools to
manipulate data, its template of predefined data type limits its ability to manage large objects. In
our implementation, the attributes of Video and Images are defined as FILE type. The attributes of
Report, Chief Complaint, Description and other attributes are defined as TEXT type. More
importantly, they can be uniformly manipulated in SQL queries.
4. International Journal of Advanced Information Technology (IJAIT) Vol. 4, No. 1, February 2014
4
Figure 1.Web-based telemedicine system Arch.[1]Figure 2.Ain Medical Telemedicine Architecture
In addition to data integration, speed of data retrieval is also a factor that affects the performance
of the telemedicine system. In this paper, a three-layer hierarchical database is created; the three
layers consist of main database, long-term database, and local database. The main database stores
medical information concerning patients who have visited within recent months. After this period,
the data are moved to a long-term database. Then the long-term database server packs the image
data according to time of creation and manages it in the DICOM media storage directory
(DICOMDIR) format, which is introduced by the American College of Radiology and the
National Electrical Manufacturers Association (ACR/NEMA)to store DICOM-formatted medical
images in permanent media[31].
The local database provides a short-term storage location forthe medical records of patients
currently visiting. It functions to reduce workload of the database server and traffic of the
network. In order to prepare the most frequently used data, the PREFETCH mechanism, which
works to reduce the data accessing time, is incorporated into the local database installed in the
medical center. During teleconsultation, the PREFETCH precedes the diagnosis and accesses
medical records according to the schedule. In telediagnosis, the medical records must also be
prefetched if the diagnosis report has not yet been completed. Moreover, the REFRESH
mechanism is also incorporated in the local database at the rural site to maintain acceptable
communication reliability. It stores the medical records of newly visiting patients in the local
database and forward these records when the communication channel has been successfully
connected. Thus, it can avoid data loss caused by failure of the communication channel.
2.4. AinMedical.com Database
1)Doctor Registration, for the doctor to become a member of the A in Medical portal, the system
requires a registration of a new user as Doctor which allows him to access the AinMedical.com
web- portal different services. The Doctor who uses website with Pre-condition having a valid
email address to complete registration. A in Medical portal sends message to new doctor to
activate his account. Also a message will be sent to A in Medical’s Administrator to approve the
new doctor account or delete it. If A in Medical’s Administrator approved the doctor registration,
A in Medical presents welcome page for New Doctor and provide link to login his account. As
indicated in Fig. (3).
5. International Journal of Advanced Information Technology (IJAIT) Vol. 4, No. 1, February 2014
5
Figure 3.Doctor Registration
2) Patient Registration, for the patient to become a member of the AinMedical.com web-portal,
the system requires a registration of a new user as Patient which allows him to access the A in
Medical portal different services. The Use Case describes the Actors as: Patient who uses website
with Pre-condition having a valid email address to complete registration. A in Medical portal
sends message to new doctor to activate his/her account. Also a message will be sent to A in
Medical.com’s Administrator (new Patient has been registered), AinMedical.com presents
welcome page for New Patient and provide link to login his account. As indicated in Fig.(4).
Figure 4. Patient Registration
6. International Journal of Advanced Information Technology (IJAIT) Vol. 4, No. 1, February 2014
6
3) Telemedicine services Activation, From Doctor side, the requirements of telemedicine services
activation needs to manage doctor's account, the doctor already activated this service for his
account then user press “Add/Manage Telemedicine service” link to activate it for the first time or
manage his data in it respectively and the flow chart appeared in Fig.(5)
Figure 5. Telemedicine services Activation
4) Doctor Manage telemedicine services & their setting (days & time-slots /cost),If Portal's
doctor needs to review/mange his telemedicine services, it requires him to login on A in Medical
Portal with his account then press “Manage Telemedicine service” link to review his telemedicine
services, add new services and modify them. If Portal's doctor needs to review/mange
telemedicine setting (days & time-slots /cost), it requires him to login on A in Medical Portal with
his account then press “Manage Telemedicine service” link to review service setting, add new
times and modify days & time-slots /cost.
Figure 6. Doctor Manage telemedicine services & settings
7. International Journal of Advanced Information Technology (IJAIT) Vol. 4, No. 1, February 2014
7
5) Doctor Manage booking requests, If Portal's doctor needs to needs to review/mange booking
requests), it requires him to login on A in Medical Portal with his account then press “Manage
Telemedicine service” to review booking requests and then the doctor can select request to review
patient's details (patient data, time, patient medical history), the doctor can change request status
or add prescription and required radiograph & tests.
Figure 7.Doctor Manage booking requests
6)Patient add basic information & medical history, From patient side, the requirements of
telemedicine services activation needs to manage doctor's account, Portal's patient need to add his
basic information. The patient enter to Telemedicine link on A in Medical Portal, then press "
Add/View medical history", and select the needed link to review/add data for (basic information,
diseases, symptoms ,pharmaceuticals, surgeries, sensitivities, radiograph, tests).
Figure 8.Patient add basic information & medical history
7) Patient makes booking &reviews his booking list, If patient needs to use telemedicine services
and make booking with one of AinMedical.com doctors, this requires the patient to review doctor
list to search for the required doctor. The patient press "book now" which beside the doctor he
8. International Journal of Advanced Information Technology (IJAIT) Vol. 4, No. 1, February 2014
8
selects, fills the form of booking then selects the time and press send. The request will be sent and
the payment taken from patient credit.
If patient needs to review his booking list. the patient enter to Telemedicine link on
AinMedical.com Portal, then user press “booking data” link & review his booking list. If the
conversation with doctor done, patient can review the prescription and the required radiographs&
tests.
Figure 9. Patient makes booking Figure 10. Patient reviews his booking list
3. CONCLUSIONS
This paper describes a telemedicine system used to provide medical services to a rural healthcare
center. Three operational modes of the telemedicine system are explored through the system
developed. In order to fulfill the requirements of medical practice, we define a PIP that functions
as a database processing element encapsulating medical information obtained during one patient
visit. A PIP-based data structure can reduce the complexity of accessing medical information. In
this study, we also integrate multimedia patient information within the same database system and
provide two kinds of user interfaces for different medical service purposes.
The medical services provided by the telemedicine system at the rural site are eagerly needed by
the elderly. The system allows the elderly to avoid traveling a long distance to get better care.
Evaluation results show that the telemedicine system is relatively feasible in the case of
teleradiology. Telemedicine has shown the capability not only to improve the quality of
healthcare, but also to increase the opportunity of continuing education for physicians at a rural
site. According to the results of the survey, the WWW environment’s features of multimedia and
hyper linking made the web-based browser suitable for displaying medical teaching materials.
Based on the system developed, there are many other aspects that can be explored in the future.
One is to add a datamining technique to the system [32]. This could allow the formulation of
9. International Journal of Advanced Information Technology (IJAIT) Vol. 4, No. 1, February 2014
9
diagnostic behaviors and build a knowledge base to assist diagnosis and medical teaching. The
other is to incorporate image compression technique to speed image transmission [33]. These
advances may help researchers to not only explore the knowledge of medical behavior, but also
expand the feasibility of the telemedicine system.
REFERENCES
[1] B. H. Guze, R. Estep, and C. Fisher, “Telemedicine: A review of its use and a proposal for application
in psychiatric consultation,” Med. Inform., vol. 20, no. 1, pp. 1–18, 1995.
[2] J. E. Cabral, Jr. and Y. Kim, “Multimedia systems for telemedicine and their communications
requirements,” IEEE Commun. Mag., July 1996, pp. 20–27.
[3] T. Paakkala, J. Aalto, V. K¨ah¨ar¨a, and S. Sepp¨anen, “Diagnostic performance of a teleradiology
system in primary health care,” Comput. Methods Programs Biomed., vol. 36, pp. 157–160, 1991.
[4] J. Viitanen, T. Sund, E. Rinde, J. Stoermer, M. Kormano, J. Heinila, J.Yliaho, and J. Ahonen, “Nordic
teleradiology development,” Comput.Methods Programs Biomed., vol. 37, pp. 273–277, 1992.
[5] H. K. Huang, “Teleradiology technologies and some service models,” Comput. Med. Imag. Graph.,
vol. 20, no. 2, pp. 59–68, 1996.
[6] O. Ratib, Y. Ligier, and J. R. Scherrer, “Digital image management and communication in medicine,”
Comput. Med. Imag. Graph., vol. 18, no.2, pp. 73–84, 1994.
[7] H. K. Huang et al., “Implementation of a large-scale picture archiving and communication system,”
Comput. Med. Imag. Graph., vol. 17, no. 1, pp. 1–11, 1993.
[8] D. F. Leotta and Y. Kim, “Requirements for picture archiving andcommunications,” IEEE Eng. Med.
Biol. Mag. , pp. 62–69, Mar. 1993.
[9] H. K. Huang, W. K. Wong, S. L. Lou, and B. K. Stewart, “Architecture of a comprehensive
radiologic imaging network,” IEEE J. Select. Areas Commun., vol. 10, pp. 1188–1196, Sept. 1992.
[10] W. J. Chimiak, “The digital radiology environment,” IEEE J. Select.AreasCommun., vol. 10, pp.
1133–1144, Sept. 1992.
[11] S. T. Treves, E. S. Hashem, B. A. Majmudar, K. Mitchell, and D. J. Michaud, “Multimedia
communications in medical imaging,” IEEE J. Select. Areas Commun., vol. 10, pp. 1121–1132, Sept.
1992.
[12] S. L. Lou, J. Wang, M. Moskowitz, T. Bazzill, and H. K. Huang, “Methods of automatically acquiring
images from digital medical systems,” Comput. Med. Imag. Graph., vol. 19, no. 4, pp. 369–376,
1995.
[13] Digital Imaging and Communications in Medicine (DICOM) Version 3.0, Amer. College
Radiologists/Nat. Elect. Manufacturers Assoc., 1993.
[14] G. Bucci, R. Detti, S. Nativi, and V. Pasqui “Loosely coupled workstations in a radiological image
information system,” Future Generation Comput. Syst., vol. 8, pp. 31–42, 1992.
[15] S. K. Mun, M. Freedman, and R. Kapur, “Image Management and communications for radiology,”
IEEE Eng. Med. Biol. Mag., pp. 70–80, Mar. 1993.
[16] G. Hartviksen, S. Akselsen, A. K. Eidsvik, S. Pedersen, and E. Rinde, “Toward a general purpose,
scaleable workstation for remote medical consultations.Experiences from use of VIDA-a still image
system for the provision of low-cost telemedicine,” Med. Inform., vol. 20, no. 1, pp. 19–33, 1995.
[17] H. Handels, C. Busch, J. Encarna¸cao C. Hahn, V. K hn, J. Miehe, S. I. P¨oppl, E. Rinast, C.
Roßmanith, F. Seibert, and A. Will, “KAMEDIN: A telemedicine system for computer supported
cooperative work and remote image analysis in radiology,” Comput. Methods Programs Biomed., vol.
52, pp. 175–183, 1997.
[18] F. R. Bartsch, M. Gerneth, and R. Schosser, “Videoconference as a tool for European inter-hospital
consultations in radiology,” in Proc. SPIE,1977, pp. 62–67.
[19] S. J. Dwyer, III, et al., “Teleradiology using switched dialup networks,” IEEE J. Select. Areas
Commun., vol. 10, pp. 1161–1172, Sept. 1992.
[20] L. Orozco-Barbosa, A. Karmouch, N. D. Georganas, and M. Goldberg, “A multimedia interhospital
communications system for medical consultations,” IEEE J. Select. Areas Commun., vol. 10, pp.
1145–1157, Sept. 1992.
[21] K. Chipman, P. Holzworth, J. Loop, N. Ransom, D. Spears, and B. Thompson, “Medical applications
in a B-ISDN field trial,” IEEE J. Select. Areas Commun., vol. 10, pp. 1173–1187, Sept. 1992.
10. International Journal of Advanced Information Technology (IJAIT) Vol. 4, No. 1, February 2014
10
[22] H. K. Huang, R. L. Arenson, S.-L. Lou, A. W. K. Wong, K. P. Andriole, T. M. Bazzill, and D. Avrin,
“Multimedia in the radiology environment:Current concept,” Comput. Med. Imag. Graph., vol. 18,
no. 1, pp. 1–10, 1994.
[23] G. F. Egan and Z.-Q.Liu, “Computers and networks in medical and healthcare systems,”
Comput.Biol. Med., vol. 25, no. 3, pp. 355–365, 1995.
[24] T. Kitanosono, Y. Kurashita, M. Honda, T. Hishida, H. Konishi, M. Mizuno, and M. Anzai, “The use
of multimedia in patient care,” Comput. Methods Programs Biomed., vol. 37, pp. 259–263, 1992.
[25] S. T. C. Wong and H. K. Huang “A hospital integrated framework for multimodality image base
management,” IEEE Trans. Syst., Man, Cybern. A, vol. 26, pp. 455–469, July 1996.
[26] R. K. Taira, B. K. Stewart, and U. Sinha, “PACS database architecture and design,” Comput. Med.
Imag. Graph., vol. 15, no. 3, pp. 171–176, 1991.
[27] S. Badaoui, V. Chameroy, and F. Aubry, “A database manager of biomedical images,” Med. Inform.,
vol. 18, no. 1, pp. 23–33, 1993.
[28] F. Pinciroli, C. Combi, and G. Pozzi, “ARCADIA: A system for the integration of angiocardiographic
data and images by an object-oriented DBMS,” Comput. Biomed.Res., vol. 28, pp. 5–23, 1995.
[29] A. Karmouch, “Multimedia distributed cooperative system,” Comput. Commun., vol. 16, pp. 568–
580, Sept. 1993.
[30] R. E. Rakel, Textbook of Family Practice, 5th ed. Philadelphia, PA: Saunders, 1995.
[31] Digital Imaging and Communications in Medicine (DICOM) Version 3.0, Amer. College
Radiologists/Nat. Elect. Manufacturers Assoc., 1993.
[32] C. T. Liu, C. C. Lin, J. M. Wong, S. K. Chiou, R. S. Chen, J. H. Chen, S. M. Hou, and T. Y. Tai,
“Design and evaluation of a telediagnosis system,” Biomed. Eng. Applicat., Basis Commun., vol. 9,
pp. 52–60, Apr. 1997.
[33] H. S. Chen et al., “Integrated medical informatics with small group teaching in medical education,”
Int. J. Med. Inform., to be published.
Author
Hafez Fouadreceivedhis BSc. degree in Electronics and communications engineering in
1993, EGYPT and received his M.Sc. and Ph.D. degrees from Ain Shams University in
2001 and 2008. His Ph.D. is dedicated to Performance Optimization of CMOS RF Power
Amplifiers for Mobile Communication systems. The M.Sc. is dedicated to Design and
Optimization of Silicon RF Front-ends For Mobile Communication Systems. He is a
researcher at the Electronics Research Institute (ERI), Ministry of Scientific Research,
Cairo, Egypt. His current research interests are Telemedicine Systems, wireless sensors
network, Bioelectronics, Bioinformatics and their applications.
International Journal of Advanced Information Technology (IJAIT) Vol. 4, No. 1, February 2014
10
[22] H. K. Huang, R. L. Arenson, S.-L. Lou, A. W. K. Wong, K. P. Andriole, T. M. Bazzill, and D. Avrin,
“Multimedia in the radiology environment:Current concept,” Comput. Med. Imag. Graph., vol. 18,
no. 1, pp. 1–10, 1994.
[23] G. F. Egan and Z.-Q.Liu, “Computers and networks in medical and healthcare systems,”
Comput.Biol. Med., vol. 25, no. 3, pp. 355–365, 1995.
[24] T. Kitanosono, Y. Kurashita, M. Honda, T. Hishida, H. Konishi, M. Mizuno, and M. Anzai, “The use
of multimedia in patient care,” Comput. Methods Programs Biomed., vol. 37, pp. 259–263, 1992.
[25] S. T. C. Wong and H. K. Huang “A hospital integrated framework for multimodality image base
management,” IEEE Trans. Syst., Man, Cybern. A, vol. 26, pp. 455–469, July 1996.
[26] R. K. Taira, B. K. Stewart, and U. Sinha, “PACS database architecture and design,” Comput. Med.
Imag. Graph., vol. 15, no. 3, pp. 171–176, 1991.
[27] S. Badaoui, V. Chameroy, and F. Aubry, “A database manager of biomedical images,” Med. Inform.,
vol. 18, no. 1, pp. 23–33, 1993.
[28] F. Pinciroli, C. Combi, and G. Pozzi, “ARCADIA: A system for the integration of angiocardiographic
data and images by an object-oriented DBMS,” Comput. Biomed.Res., vol. 28, pp. 5–23, 1995.
[29] A. Karmouch, “Multimedia distributed cooperative system,” Comput. Commun., vol. 16, pp. 568–
580, Sept. 1993.
[30] R. E. Rakel, Textbook of Family Practice, 5th ed. Philadelphia, PA: Saunders, 1995.
[31] Digital Imaging and Communications in Medicine (DICOM) Version 3.0, Amer. College
Radiologists/Nat. Elect. Manufacturers Assoc., 1993.
[32] C. T. Liu, C. C. Lin, J. M. Wong, S. K. Chiou, R. S. Chen, J. H. Chen, S. M. Hou, and T. Y. Tai,
“Design and evaluation of a telediagnosis system,” Biomed. Eng. Applicat., Basis Commun., vol. 9,
pp. 52–60, Apr. 1997.
[33] H. S. Chen et al., “Integrated medical informatics with small group teaching in medical education,”
Int. J. Med. Inform., to be published.
Author
Hafez Fouadreceivedhis BSc. degree in Electronics and communications engineering in
1993, EGYPT and received his M.Sc. and Ph.D. degrees from Ain Shams University in
2001 and 2008. His Ph.D. is dedicated to Performance Optimization of CMOS RF Power
Amplifiers for Mobile Communication systems. The M.Sc. is dedicated to Design and
Optimization of Silicon RF Front-ends For Mobile Communication Systems. He is a
researcher at the Electronics Research Institute (ERI), Ministry of Scientific Research,
Cairo, Egypt. His current research interests are Telemedicine Systems, wireless sensors
network, Bioelectronics, Bioinformatics and their applications.
International Journal of Advanced Information Technology (IJAIT) Vol. 4, No. 1, February 2014
10
[22] H. K. Huang, R. L. Arenson, S.-L. Lou, A. W. K. Wong, K. P. Andriole, T. M. Bazzill, and D. Avrin,
“Multimedia in the radiology environment:Current concept,” Comput. Med. Imag. Graph., vol. 18,
no. 1, pp. 1–10, 1994.
[23] G. F. Egan and Z.-Q.Liu, “Computers and networks in medical and healthcare systems,”
Comput.Biol. Med., vol. 25, no. 3, pp. 355–365, 1995.
[24] T. Kitanosono, Y. Kurashita, M. Honda, T. Hishida, H. Konishi, M. Mizuno, and M. Anzai, “The use
of multimedia in patient care,” Comput. Methods Programs Biomed., vol. 37, pp. 259–263, 1992.
[25] S. T. C. Wong and H. K. Huang “A hospital integrated framework for multimodality image base
management,” IEEE Trans. Syst., Man, Cybern. A, vol. 26, pp. 455–469, July 1996.
[26] R. K. Taira, B. K. Stewart, and U. Sinha, “PACS database architecture and design,” Comput. Med.
Imag. Graph., vol. 15, no. 3, pp. 171–176, 1991.
[27] S. Badaoui, V. Chameroy, and F. Aubry, “A database manager of biomedical images,” Med. Inform.,
vol. 18, no. 1, pp. 23–33, 1993.
[28] F. Pinciroli, C. Combi, and G. Pozzi, “ARCADIA: A system for the integration of angiocardiographic
data and images by an object-oriented DBMS,” Comput. Biomed.Res., vol. 28, pp. 5–23, 1995.
[29] A. Karmouch, “Multimedia distributed cooperative system,” Comput. Commun., vol. 16, pp. 568–
580, Sept. 1993.
[30] R. E. Rakel, Textbook of Family Practice, 5th ed. Philadelphia, PA: Saunders, 1995.
[31] Digital Imaging and Communications in Medicine (DICOM) Version 3.0, Amer. College
Radiologists/Nat. Elect. Manufacturers Assoc., 1993.
[32] C. T. Liu, C. C. Lin, J. M. Wong, S. K. Chiou, R. S. Chen, J. H. Chen, S. M. Hou, and T. Y. Tai,
“Design and evaluation of a telediagnosis system,” Biomed. Eng. Applicat., Basis Commun., vol. 9,
pp. 52–60, Apr. 1997.
[33] H. S. Chen et al., “Integrated medical informatics with small group teaching in medical education,”
Int. J. Med. Inform., to be published.
Author
Hafez Fouadreceivedhis BSc. degree in Electronics and communications engineering in
1993, EGYPT and received his M.Sc. and Ph.D. degrees from Ain Shams University in
2001 and 2008. His Ph.D. is dedicated to Performance Optimization of CMOS RF Power
Amplifiers for Mobile Communication systems. The M.Sc. is dedicated to Design and
Optimization of Silicon RF Front-ends For Mobile Communication Systems. He is a
researcher at the Electronics Research Institute (ERI), Ministry of Scientific Research,
Cairo, Egypt. His current research interests are Telemedicine Systems, wireless sensors
network, Bioelectronics, Bioinformatics and their applications.