The document discusses dental informatics, including its definition as the application of computer and information science to improve dental practice, research, education, and management. It provides an overview of the discipline of dental informatics, its scope, and various applications in administrative, clinical, educational, and research domains. Examples of clinical informatics applications discussed include electronic oral health records, digital radiography, 3D scanning and milling, image-guided implantology, and teledentistry.
eBook - Top Six Ways an Integrated EDR Improves Your Health CenterNextGen Healthcare
If you have doubts about whether you need an electronic dental record (EDR), look no further. This eBook packs the punch you need to see how the right EDR can really revolutionize your practice.
Dental informatics is the application of computer and information science to improve dental practice, research, education, and management. It draws upon fields like cognitive science, computer science, information science, and telecommunications. Dental informatics can improve the effectiveness, efficiency, quality of care, patient experience, and office management through applications like electronic oral health records, digital radiography, 3D imaging and modeling, teledentistry, and dental education simulations. Challenges include ensuring quality information, provision of care, licensure, reimbursement, and defining emerging roles for professionals with new technologies.
1) The document discusses the use of artificial intelligence in orthodontics, including applications like automated cephalometric analysis, skeletal classification, predicting orthodontic treatment needs, and 3D tooth segmentation.
2) AI technologies like convolutional neural networks, artificial neural networks, and deep learning are being used in these orthodontic applications.
3) While AI is proving accurate and can help practitioners make decisions faster, limitations include cost, data protection concerns, and ensuring AI systems do not replace human clinicians for serious medical decisions.
dtg is a design and technology group led by Eli Ganon that provides services related to technology strategy, transformation, analytics, market research, product development, and regulatory compliance across multiple sectors including healthcare, life sciences, manufacturing and medical devices. dtg works with clients to develop innovative solutions through Eli's expertise in areas such as informatics, analytics, medical imaging, electronic health records and medical devices.
The Indian Dental Academy is the Leader in continuing dental education , training dentists in all aspects of dentistry and
offering a wide range of dental certified courses in different formats.for more details please visit
www.indiandentalacademy.com
Artificial intelligence has various applications in oral and maxillofacial surgery including robotics, navigation surgery, virtual reality, and augmented reality. AI-based systems use machine learning and neural networks to aid in clinical decision making, diagnosis, treatment planning, and predicting outcomes. Recent advances in AI, virtual reality, augmented reality, and surgical navigation have improved precision and simplified complex procedures in oral and maxillofacial surgery. However, more data and training is still needed for AI to reach its full potential.
The document discusses standards and coding systems used in biomedical and health informatics. It provides background on the speaker and their qualifications in the fields of medicine and health informatics. It then discusses why healthcare information standards are needed, providing examples of different types of standards including unique identifiers, standard data sets, vocabularies and terminologies, and exchange standards for messages and documents.
eBook - Top Six Ways an Integrated EDR Improves Your Health CenterNextGen Healthcare
If you have doubts about whether you need an electronic dental record (EDR), look no further. This eBook packs the punch you need to see how the right EDR can really revolutionize your practice.
Dental informatics is the application of computer and information science to improve dental practice, research, education, and management. It draws upon fields like cognitive science, computer science, information science, and telecommunications. Dental informatics can improve the effectiveness, efficiency, quality of care, patient experience, and office management through applications like electronic oral health records, digital radiography, 3D imaging and modeling, teledentistry, and dental education simulations. Challenges include ensuring quality information, provision of care, licensure, reimbursement, and defining emerging roles for professionals with new technologies.
1) The document discusses the use of artificial intelligence in orthodontics, including applications like automated cephalometric analysis, skeletal classification, predicting orthodontic treatment needs, and 3D tooth segmentation.
2) AI technologies like convolutional neural networks, artificial neural networks, and deep learning are being used in these orthodontic applications.
3) While AI is proving accurate and can help practitioners make decisions faster, limitations include cost, data protection concerns, and ensuring AI systems do not replace human clinicians for serious medical decisions.
dtg is a design and technology group led by Eli Ganon that provides services related to technology strategy, transformation, analytics, market research, product development, and regulatory compliance across multiple sectors including healthcare, life sciences, manufacturing and medical devices. dtg works with clients to develop innovative solutions through Eli's expertise in areas such as informatics, analytics, medical imaging, electronic health records and medical devices.
The Indian Dental Academy is the Leader in continuing dental education , training dentists in all aspects of dentistry and
offering a wide range of dental certified courses in different formats.for more details please visit
www.indiandentalacademy.com
Artificial intelligence has various applications in oral and maxillofacial surgery including robotics, navigation surgery, virtual reality, and augmented reality. AI-based systems use machine learning and neural networks to aid in clinical decision making, diagnosis, treatment planning, and predicting outcomes. Recent advances in AI, virtual reality, augmented reality, and surgical navigation have improved precision and simplified complex procedures in oral and maxillofacial surgery. However, more data and training is still needed for AI to reach its full potential.
The document discusses standards and coding systems used in biomedical and health informatics. It provides background on the speaker and their qualifications in the fields of medicine and health informatics. It then discusses why healthcare information standards are needed, providing examples of different types of standards including unique identifiers, standard data sets, vocabularies and terminologies, and exchange standards for messages and documents.
Voice based Application as Medicine Spotter for Visually ImpairedIRJET Journal
This paper proposes a voice-based mobile application to help visually impaired individuals identify their medicines independently. The application uses image processing and text recognition on photos of medicine packages taken with the phone's camera to identify the medicine name. It then checks the user's prescription to determine if it is time to take that medicine and outputs the quantity to take via voice. This allows visually impaired people to identify their medicines without assistance and ensure they are taking the correct dose at the right time. The proposed application is designed to be easy for visually impaired users to operate via voice input and output.
MEDICAL IMAGES AUTHENTICATION THROUGH WATERMARKING PRESERVING ROIhiij
Telemedicine is a well-known application where enormous amount of medical data need to be securely
transferred over the public network and manipulate effectively. Medical image watermarking is an
appropriate method used for enhancing security and authentication of medical data, which is crucial and
used for further diagnosis and reference. This project focuses on the study of medical image
watermarking methods for protecting and authenticating medical data. Additionally, it covers algorithm
for application of water marking technique on Region of Non Interest (RONI) of the medical image
preserving Region of Interest (ROI). The medical images can be transferred securely by embedding
watermarks in RONI allowing verification of the legitimate changes at the receiving end without affecting
ROI. Segmentation plays an important role in medical image processing for separating the ROI from
medical image. The proposed system separate the ROI from medical image by GUI based approach,
which works for all types of medical images. The experimental results show the satisfactory performance
of the system to authenticate the medical images preserving ROI.
This document provides an overview of health information technology (IT) and electronic health (eHealth). It discusses how information is prevalent in healthcare and highlights several landmark reports from the Institute of Medicine calling for healthcare reform and emphasizing the role of health IT in improving patient safety. The document describes various forms of health IT including electronic health records, computerized provider order entry, clinical decision support systems, and health information exchange. It explains how health IT can help guide clinicians' decisions and reduce errors, while also noting potential risks such as alert fatigue and workarounds.
This document discusses digital health transformation and the concept of a "smart hospital". It begins by looking at various technologies like artificial intelligence, cloud computing, the internet of things, and how they are impacting healthcare. It then defines what a smart hospital is, differentiating it from just a digital or paperless hospital. Specifically, a smart hospital leverages health information technology to improve the quality of care by making it safer, more timely, effective, patient-centered and efficient. The document outlines how technologies like electronic health records, computerized physician order entry, and clinical decision support systems can help hospitals achieve these goals and move towards becoming truly smart.
Confidential 1450 physician_powerpoint_emr_ver 12-23-08Dragon Medical
The document discusses the challenges of documenting care in an electronic medical record (EMR) and presents the Dragon Medical solution as a way to speech enable EMRs. It notes that EMR adoption is rapidly increasing and documentation requirements are rising to maintain reimbursement levels. Template-based EMR notes lack narrative and decision making. The Dragon Medical solution allows physicians to dictate in their own words within the EMR, improving productivity and reimbursement while eliminating transcription costs. Case studies demonstrate increases in productivity, quality of care, and cost savings from implementing Dragon Medical with EMRs.
Evaluating spatial and frequency domain enhancement techniques on dental imag...IJECEIAES
Dental imaging provides the patient's anatomical details for the dental implant based on the maxillofacial structure and the two-dimensional geometric projection, helping clinical experts decide whether the implant surgery is suitable for a particular patient. Dental images often suffer from problems associated with random noise and low contrast factors, which need effective preprocessing operations. However, each enhancement technique comes with some advantages and limitations. Therefore, choosing a suitable image enhancement method always a difficult task. In this paper, a universal framework is proposed that integrates the functionality of various enhancement mechanisms so that dentists can select a suitable method of their own choice to improve the quality of dental image for the implant procedure. The proposed framework evaluates the effectiveness of both frequency domain enhancement and spatial domain enhancement techniques on dental images. The selection of the best enhancement method further depends on the output image perceptibility responses, peak signal-to-noise ratio (PSNR), and sharpness. The proposed framework offers a flexible and scalable approach to the dental expert to perform enhancement of a dental image according to visual image features and different enhancement requirements.
Digital technologies are disrupting healthcare through wearable devices, sensors, and telemedicine. Wearables can monitor vital signs, track activity, and deliver therapies. Sensors can be embedded in materials like plasters to continuously monitor health metrics. Devices also enable remote monitoring and virtual consultations. While these technologies offer benefits like early detection and increased access to care, their adoption faces challenges regarding user experience, clinical validation, and safety that require further research.
1. The document outlines a presentation about the impact of computer science and robotics in medicine, including topics like bioinformatics, robotics, and applications like the Da Vinci surgical robot.
2. It provides details on bioinformatics, describing it as using information gathering and validation to translate medical data into practices. It also gives an overview of the Da Vinci surgical robot and its key components that enhance precision and minimize tissue damage.
3. The presentation aims to understand public perspectives on emerging technologies in healthcare, with a survey asking about the job market for doctors by 2020 and trust in robotic surgery.
A new perspective of refractive error calculation with mobile application IJECEIAES
In many situations, not standardized and limited access to eye health care in several regions of Indonesia becomes the main challenge for myopia patients to measure and monitor their current refractive error condition. Many apps were proposed to provide low-cost alternative measurement tools rather than expensive tools such as Phoropter with Snellen chart and Retinoscopy, but still, those apps need an Internet connection and manually complex steps to operate. These conditions make myopia patients reluctant to use this kind of service. In this regard, we propose an intuitive diopter level measurement app based on mobile application setup, which implements the concept of measure the user face to smartphone screen distance for the rapid diopter calculation processes and at the same time provides a low-cost alternative refractive measurement tool. This paper highlights our experiences when developing a mobile application that can help patients with myopia measuring their blur line distances and evaluate their diopter levels independently. We conduct a number of human trials with the device on a controlled environment to demonstrate the ability of the proposed app to measure the diopter level. The experimental results show that the proposed app is quite successful in measuring the diopter level of myopia patients with a relatively small range of calculation errors compared to optometrist measurement results.
(2017/06)Practical points of deep learning for medical imagingKyuhwan Jung
This document provides an overview of deep learning and its applications in medical imaging. It discusses key topics such as the definition of artificial intelligence, a brief history of neural networks and machine learning, and how deep learning is driving breakthroughs in tasks like visual and speech recognition. The document also addresses challenges in medical data analysis using deep learning, such as how to handle limited data or annotations. It provides examples of techniques used to address these challenges, such as data augmentation, transfer learning, and weakly supervised learning.
Cerner Corporation is a large healthcare IT company based in Kansas City that develops electronic medical record systems like Cerner Millennium and the iAware platform. The document discusses engineering career opportunities at Cerner, including software engineering roles developing applications and system engineering roles overseeing implementations. It also provides background on Cerner's mission and solutions that help clinicians improve healthcare delivery and community health.
Disruptors in the Medical Imaging IndustryBill Kelly
An overview of the Disruptors in the Medical Imaging Market. This free webinar will also give you more insight on the various factors that influence the market. We touch on results from a survey of a survey of 147 radiologists highlight the importance of reimbursement changes –both “appropriateness” measures and value-based medicine – as the most significant factors that will impact the imaging market.
The document describes features of a smart hospital management system, including security cameras, access controls, alarm systems, public address systems, integrated patient management systems, room displays, bedside controllers, RFID tagging, nurse stations, laboratory integration, ward management, emergency rooms, temperature controls, nursery room automation, and smart bathrooms. The system aims to provide efficient patient care, access to medical records, security, communication, and automation throughout the hospital.
Importance of Patient voice helps healthcare providers and facilities offer better healthcare delivery. It helps them understand how their patients truly feel, their needs, expectations, and concerns during every point of the care journey. Analyzing voice of the patient data allows healthcare professionals to leverage the feedback data not only for better operational aspects but also for diagnostic needs. These insights thus gained can help shape strategic treatment plans, even as healthcare providers and decision makers use data-backed information to build the foundation of patient-centric healthcare.
This document discusses applying deep learning techniques to medical data. It notes that medical data presents unique challenges compared to typical deep learning datasets, such as unclear or unbalanced annotations, and differences between medical images and other image domains. It explores approaches that have been used to address medical data issues, such as using more data, pre-trained models with fine-tuning, different network architectures, and incorporating additional context data from patient records. The document emphasizes that solving medical AI problems requires collaboration between AI and medical experts to effectively leverage both data and domain expertise.
Clinical Data Collaboration Across the Enterprise Carestream
In addition to the CARESTREAM Vue PACS installed in 2003, the hospital has implemented full electronic ADT and paperless Ancillaries, EMR Adoption, full electronic medication CPOE and a Structured and Document Clinical Repository (connected to regional EHR).
Despite the completeness of this IT infrastructure, the hospital was still searching for an optimal solution for an integrated clinical image repository and distribution system.
Clinical Trial Design and Artificial Intelligence | Pepgra.comPEPGRA Healthcare
Clinical trials take up the last half of the 10 – 15 year, 1.5 – 2.0 billion USD, cycle of development just for introducing a new drug within a market.
1. AI and its Evolution
2. AI in Clinical Trials
To Continue Reading: https://bit.ly/2W01UDQ
Contact Us:
Website : https://bit.ly/33Fwsye
Email us: sales.cro@pepgra.com
Whatsapp: +91 9884350006
영상기반 딥러닝 의료 분야 응용 (KIST 김영준) - 2017 대한의료영상학회 발표Youngjun Kim
This document summarizes deep learning applications in medical imaging at the Korea Institute of Science and Technology. It begins with an introduction to deep learning and examples of medical applications such as disease diagnosis from medical images using convolutional neural networks. It then discusses KIST's research applying deep learning to tasks such as rotator cuff tear diagnosis from MRI and surgical planning software. The document concludes by noting some of KIST's publications in using deep learning for medical image analysis and registration.
Introduction to Health Informatics and Health IT (Part 1) (February 10, 2021)Nawanan Theera-Ampornpunt
Presented at the 11th Healthcare CIO Certificate Program, School of Hospital Management, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok, Thailand on February 10, 2021
[DSC Adria 23]Franko Hrzic Challenges in Medical Image Diagnostics.pdfDataScienceConferenc1
This document outlines four key challenges in medical image diagnostics using artificial intelligence:
1) Data versatility and different peculiarities between patients which can introduce biases. This includes issues like rare diseases with unbalanced data.
2) Difficulties with data collection due to scattered data across countries with different privacy laws, and challenges ensuring high quality labeling.
3) Restrictions of using private medical data through federated learning due to costs and legal issues transferring data.
4) Ensuring AI systems are trustworthy by enabling explainability when models fail, to determine if it is a data or model issue. The goal is to develop laws, technologies and methods like explainable AI to address these challenges.
The document discusses information retrieval and summarizes key points about data, information, knowledge, and informatics. It provides definitions of information retrieval and discusses challenges in retrieving information from large, unstructured collections. It also summarizes the scope of informatics as focusing on representing, processing, and communicating information in natural and artificial systems.
Voice based Application as Medicine Spotter for Visually ImpairedIRJET Journal
This paper proposes a voice-based mobile application to help visually impaired individuals identify their medicines independently. The application uses image processing and text recognition on photos of medicine packages taken with the phone's camera to identify the medicine name. It then checks the user's prescription to determine if it is time to take that medicine and outputs the quantity to take via voice. This allows visually impaired people to identify their medicines without assistance and ensure they are taking the correct dose at the right time. The proposed application is designed to be easy for visually impaired users to operate via voice input and output.
MEDICAL IMAGES AUTHENTICATION THROUGH WATERMARKING PRESERVING ROIhiij
Telemedicine is a well-known application where enormous amount of medical data need to be securely
transferred over the public network and manipulate effectively. Medical image watermarking is an
appropriate method used for enhancing security and authentication of medical data, which is crucial and
used for further diagnosis and reference. This project focuses on the study of medical image
watermarking methods for protecting and authenticating medical data. Additionally, it covers algorithm
for application of water marking technique on Region of Non Interest (RONI) of the medical image
preserving Region of Interest (ROI). The medical images can be transferred securely by embedding
watermarks in RONI allowing verification of the legitimate changes at the receiving end without affecting
ROI. Segmentation plays an important role in medical image processing for separating the ROI from
medical image. The proposed system separate the ROI from medical image by GUI based approach,
which works for all types of medical images. The experimental results show the satisfactory performance
of the system to authenticate the medical images preserving ROI.
This document provides an overview of health information technology (IT) and electronic health (eHealth). It discusses how information is prevalent in healthcare and highlights several landmark reports from the Institute of Medicine calling for healthcare reform and emphasizing the role of health IT in improving patient safety. The document describes various forms of health IT including electronic health records, computerized provider order entry, clinical decision support systems, and health information exchange. It explains how health IT can help guide clinicians' decisions and reduce errors, while also noting potential risks such as alert fatigue and workarounds.
This document discusses digital health transformation and the concept of a "smart hospital". It begins by looking at various technologies like artificial intelligence, cloud computing, the internet of things, and how they are impacting healthcare. It then defines what a smart hospital is, differentiating it from just a digital or paperless hospital. Specifically, a smart hospital leverages health information technology to improve the quality of care by making it safer, more timely, effective, patient-centered and efficient. The document outlines how technologies like electronic health records, computerized physician order entry, and clinical decision support systems can help hospitals achieve these goals and move towards becoming truly smart.
Confidential 1450 physician_powerpoint_emr_ver 12-23-08Dragon Medical
The document discusses the challenges of documenting care in an electronic medical record (EMR) and presents the Dragon Medical solution as a way to speech enable EMRs. It notes that EMR adoption is rapidly increasing and documentation requirements are rising to maintain reimbursement levels. Template-based EMR notes lack narrative and decision making. The Dragon Medical solution allows physicians to dictate in their own words within the EMR, improving productivity and reimbursement while eliminating transcription costs. Case studies demonstrate increases in productivity, quality of care, and cost savings from implementing Dragon Medical with EMRs.
Evaluating spatial and frequency domain enhancement techniques on dental imag...IJECEIAES
Dental imaging provides the patient's anatomical details for the dental implant based on the maxillofacial structure and the two-dimensional geometric projection, helping clinical experts decide whether the implant surgery is suitable for a particular patient. Dental images often suffer from problems associated with random noise and low contrast factors, which need effective preprocessing operations. However, each enhancement technique comes with some advantages and limitations. Therefore, choosing a suitable image enhancement method always a difficult task. In this paper, a universal framework is proposed that integrates the functionality of various enhancement mechanisms so that dentists can select a suitable method of their own choice to improve the quality of dental image for the implant procedure. The proposed framework evaluates the effectiveness of both frequency domain enhancement and spatial domain enhancement techniques on dental images. The selection of the best enhancement method further depends on the output image perceptibility responses, peak signal-to-noise ratio (PSNR), and sharpness. The proposed framework offers a flexible and scalable approach to the dental expert to perform enhancement of a dental image according to visual image features and different enhancement requirements.
Digital technologies are disrupting healthcare through wearable devices, sensors, and telemedicine. Wearables can monitor vital signs, track activity, and deliver therapies. Sensors can be embedded in materials like plasters to continuously monitor health metrics. Devices also enable remote monitoring and virtual consultations. While these technologies offer benefits like early detection and increased access to care, their adoption faces challenges regarding user experience, clinical validation, and safety that require further research.
1. The document outlines a presentation about the impact of computer science and robotics in medicine, including topics like bioinformatics, robotics, and applications like the Da Vinci surgical robot.
2. It provides details on bioinformatics, describing it as using information gathering and validation to translate medical data into practices. It also gives an overview of the Da Vinci surgical robot and its key components that enhance precision and minimize tissue damage.
3. The presentation aims to understand public perspectives on emerging technologies in healthcare, with a survey asking about the job market for doctors by 2020 and trust in robotic surgery.
A new perspective of refractive error calculation with mobile application IJECEIAES
In many situations, not standardized and limited access to eye health care in several regions of Indonesia becomes the main challenge for myopia patients to measure and monitor their current refractive error condition. Many apps were proposed to provide low-cost alternative measurement tools rather than expensive tools such as Phoropter with Snellen chart and Retinoscopy, but still, those apps need an Internet connection and manually complex steps to operate. These conditions make myopia patients reluctant to use this kind of service. In this regard, we propose an intuitive diopter level measurement app based on mobile application setup, which implements the concept of measure the user face to smartphone screen distance for the rapid diopter calculation processes and at the same time provides a low-cost alternative refractive measurement tool. This paper highlights our experiences when developing a mobile application that can help patients with myopia measuring their blur line distances and evaluate their diopter levels independently. We conduct a number of human trials with the device on a controlled environment to demonstrate the ability of the proposed app to measure the diopter level. The experimental results show that the proposed app is quite successful in measuring the diopter level of myopia patients with a relatively small range of calculation errors compared to optometrist measurement results.
(2017/06)Practical points of deep learning for medical imagingKyuhwan Jung
This document provides an overview of deep learning and its applications in medical imaging. It discusses key topics such as the definition of artificial intelligence, a brief history of neural networks and machine learning, and how deep learning is driving breakthroughs in tasks like visual and speech recognition. The document also addresses challenges in medical data analysis using deep learning, such as how to handle limited data or annotations. It provides examples of techniques used to address these challenges, such as data augmentation, transfer learning, and weakly supervised learning.
Cerner Corporation is a large healthcare IT company based in Kansas City that develops electronic medical record systems like Cerner Millennium and the iAware platform. The document discusses engineering career opportunities at Cerner, including software engineering roles developing applications and system engineering roles overseeing implementations. It also provides background on Cerner's mission and solutions that help clinicians improve healthcare delivery and community health.
Disruptors in the Medical Imaging IndustryBill Kelly
An overview of the Disruptors in the Medical Imaging Market. This free webinar will also give you more insight on the various factors that influence the market. We touch on results from a survey of a survey of 147 radiologists highlight the importance of reimbursement changes –both “appropriateness” measures and value-based medicine – as the most significant factors that will impact the imaging market.
The document describes features of a smart hospital management system, including security cameras, access controls, alarm systems, public address systems, integrated patient management systems, room displays, bedside controllers, RFID tagging, nurse stations, laboratory integration, ward management, emergency rooms, temperature controls, nursery room automation, and smart bathrooms. The system aims to provide efficient patient care, access to medical records, security, communication, and automation throughout the hospital.
Importance of Patient voice helps healthcare providers and facilities offer better healthcare delivery. It helps them understand how their patients truly feel, their needs, expectations, and concerns during every point of the care journey. Analyzing voice of the patient data allows healthcare professionals to leverage the feedback data not only for better operational aspects but also for diagnostic needs. These insights thus gained can help shape strategic treatment plans, even as healthcare providers and decision makers use data-backed information to build the foundation of patient-centric healthcare.
This document discusses applying deep learning techniques to medical data. It notes that medical data presents unique challenges compared to typical deep learning datasets, such as unclear or unbalanced annotations, and differences between medical images and other image domains. It explores approaches that have been used to address medical data issues, such as using more data, pre-trained models with fine-tuning, different network architectures, and incorporating additional context data from patient records. The document emphasizes that solving medical AI problems requires collaboration between AI and medical experts to effectively leverage both data and domain expertise.
Clinical Data Collaboration Across the Enterprise Carestream
In addition to the CARESTREAM Vue PACS installed in 2003, the hospital has implemented full electronic ADT and paperless Ancillaries, EMR Adoption, full electronic medication CPOE and a Structured and Document Clinical Repository (connected to regional EHR).
Despite the completeness of this IT infrastructure, the hospital was still searching for an optimal solution for an integrated clinical image repository and distribution system.
Clinical Trial Design and Artificial Intelligence | Pepgra.comPEPGRA Healthcare
Clinical trials take up the last half of the 10 – 15 year, 1.5 – 2.0 billion USD, cycle of development just for introducing a new drug within a market.
1. AI and its Evolution
2. AI in Clinical Trials
To Continue Reading: https://bit.ly/2W01UDQ
Contact Us:
Website : https://bit.ly/33Fwsye
Email us: sales.cro@pepgra.com
Whatsapp: +91 9884350006
영상기반 딥러닝 의료 분야 응용 (KIST 김영준) - 2017 대한의료영상학회 발표Youngjun Kim
This document summarizes deep learning applications in medical imaging at the Korea Institute of Science and Technology. It begins with an introduction to deep learning and examples of medical applications such as disease diagnosis from medical images using convolutional neural networks. It then discusses KIST's research applying deep learning to tasks such as rotator cuff tear diagnosis from MRI and surgical planning software. The document concludes by noting some of KIST's publications in using deep learning for medical image analysis and registration.
Introduction to Health Informatics and Health IT (Part 1) (February 10, 2021)Nawanan Theera-Ampornpunt
Presented at the 11th Healthcare CIO Certificate Program, School of Hospital Management, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok, Thailand on February 10, 2021
[DSC Adria 23]Franko Hrzic Challenges in Medical Image Diagnostics.pdfDataScienceConferenc1
This document outlines four key challenges in medical image diagnostics using artificial intelligence:
1) Data versatility and different peculiarities between patients which can introduce biases. This includes issues like rare diseases with unbalanced data.
2) Difficulties with data collection due to scattered data across countries with different privacy laws, and challenges ensuring high quality labeling.
3) Restrictions of using private medical data through federated learning due to costs and legal issues transferring data.
4) Ensuring AI systems are trustworthy by enabling explainability when models fail, to determine if it is a data or model issue. The goal is to develop laws, technologies and methods like explainable AI to address these challenges.
The document discusses information retrieval and summarizes key points about data, information, knowledge, and informatics. It provides definitions of information retrieval and discusses challenges in retrieving information from large, unstructured collections. It also summarizes the scope of informatics as focusing on representing, processing, and communicating information in natural and artificial systems.
presentation 2024 . New prescription presentationRahatKhan583209
1) The document is a presentation on the topic of informatics, its definition, origins, fundamental aspects, and applications.
2) Informatics is defined as the science of information, involving the representation, processing, and communication of information in natural and engineered systems with computational, cognitive and social aspects.
3) The origins of informatics date back to the 1960s and it has since been applied in various academic and professional fields such as biology, healthcare, law, management, and more.
Themes and objectives:
To position FAIR as a key enabler to automate and accelerate R&D process workflows
FAIR Implementation within the context of a use case
Grounded in precise outcomes (e.g. faster and bigger science / more reuse of data to enhance value / increased ability to share data for collaboration and partnership)
To make data actionable through FAIR interoperability
Speakers:
Mathew Woodwark,Head of Data Infrastructure and Tools, Data Science & AI, AstraZeneca
Erik Schultes, International Science Coordinator, GO-FAIR
Georges Heiter, Founder & CEO, Databiology
FINGERNAIL DISORDER DETECTION FOR DISEASE ANALYSISShiraz316
The document describes the development of an AI model using deep learning techniques to detect nail disorders for disease analysis. The proposed model uses the YOLOv4 object detection framework and is trained on a dataset of 12,000 annotated nail disorder images from 12 classes. The model architecture includes 106 convolutional layers and is trained over multiple batches to optimize detection of the nail disorders. Results show the model achieves high precision and recall scores, indicating it can accurately detect different nail disorders.
Artificial intelligence in health care by Islam salama " Saimo#BoOm "Dr-Islam Salama
A Lecture about basics and concepts of Artificial Intelligence in health care & there applications
محاضرة عامة حول الذكاء الإصطناعي وأساسياته في الرعاية الصحية والطبية وتطبيقاته
Theera-Ampornpunt N. The intersection of ICT and health informatics research. Presented at: Faculty of ICT, Mahidol University; 2012 Feb 24; Bangkok, Thailand.
This document discusses knowledge engineering for health and big data. It notes that the rate of data generation is changing but complexity, requirement to use data, and mass of useless data are stable. Knowledge engineering was first defined in 1983 as integrating knowledge into computer systems to solve complex problems. The document discusses building a knowledge engineering community and notes a need for standards around semantics, syntax, technology, and quality. It advocates for a knowledge extraction approach rather than data warehouses and discusses architectural concepts, policy and strategy considerations, and acknowledges GEN2PHEN partners and funding sources.
Artificial intelligence has the potential to transform dentistry. It can help with tasks like scheduling appointments, taking patient histories, and assisting with diagnoses and treatment planning. AI uses machine learning algorithms that learn from large amounts of dental data to help detect issues in radiographs and identify oral diseases. While AI shows promise in many areas like orthodontics, restorative dentistry, and oral pathology, challenges remain around data privacy, system complexity, and ensuring AI outcomes can be readily applied in clinical practice. Overall, AI aims to enhance the work of dental professionals by allowing for more accurate, consistent analyses and diagnoses, not replace human expertise.
An introduction to dentistry in the digital ageAmit Paryag
An overview of current technlogies available and an overview of imprortant concerns about getting into dentistry in the digital age. The content herein is referenced as much as possible and disemminated without charge for discussion and eduation purposes.
Deep-learning-or-health-informatics-recent-trends-and-future-directions By Ra...raihansikdar
Deep learning techniques show promise in developing intelligent applications for healthcare and health informatics due to the large amounts of data available. Deep learning can be used for disease prediction by learning patterns in data and images to replicate medical practitioners' decision making. It also aids in data visualization by enabling analysis and visualization of medical images. Deep learning assists technology development by processing biomedical signals for applications like brain-computer interfaces and prosthetics. However, challenges remain around data preprocessing, feature engineering, reliability of results, and handling high-dimensional data.
A Comprehensive Overview of Advance Techniques, Applications and Challenges i...IRJTAE
— The field of data science uses scientific methods, algorithms, processes, and systems to extract
insights and knowledge from structured and unstructured data. It combines principles from mathematics,
statistics, computer science, and domain expertise to analyse, interpret, and present data in meaningful ways. Its
primary aim is to uncover patterns, trends, and correlations across various domains to aid in making informed
decisions, predictions, and optimizations. Data science encompasses data collection, cleaning, analysis,
interpretation, and communication of findings. Techniques such as machine learning, statistical analysis, data
mining, and data visualization are commonly employed to derive valuable insights and solve complex problems.
Data scientists use programming languages and tools to manage large volumes of data, transforming raw
information into actionable intelligence, driving innovation, and enabling evidence-based decision-making in
businesses, research, and various other applications. This review seeks to provide a valuable resource for
researchers, practitioners, and enthusiasts who wish to gain in-depth knowledge and understanding of data
science and its implications for the ever-evolving data-driven world.
Emerging Frontiers of Forensic Odontology: Implications for Civil and Crimina...Arka95
Forensic odontology stands at the forefront of modern forensic science, offering unique
insights into human identification and criminal investigations. In India, where diverse
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profound implications for both civil and criminal sectors like dental identification, personal
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interdisciplinary approaches to enhance the integration of forensic odontology into civil and
criminal investigations, ultimately contributing to the advancement of forensic science and the
pursuit of justice in India.
This document discusses interdisciplinary research in supply chain management. It begins with opening remarks and then observes that digital transformation is disrupting traditional research approaches and requiring more collaborative work. Supply chain management provides opportunities for integration across disciplines due to concerns like material, information and money flows that cut across boundaries. Interdisciplinary research is important for advancing knowledge, enhancing teaching quality, and making societal impacts. Examples of interdisciplinary research experiences are shared, like exploring the supply chain of medical devices and dental implants. Big opportunities for interdisciplinary research are discussed, such as in the contexts of smart cities and waste management initiatives. Prerequisites for interdisciplinary research include changing mindsets, learning across disciplines, and keeping societal impacts in view rather than
This document provides information about a computational intelligence and soft computing course including the instructor's contact information, class times, required text, and an overview of upcoming lectures on data mining with neural networks. It then discusses key issues in data mining such as theory, methods/algorithms, processes, applications, and tools/techniques. Several example data mining projects are also summarized along with homework and exam due dates for the course.
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Join Jeff Kelly, Pivotal’s Big Data Strategist and Chris Roche, Aridhia’s CEO, to learn how Big Data and data science are being applied to clinical research. Learn…
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The increasing sophistication of modern medicine, a seemingly endless supply of data, and the ability to perform large-scale computation is transforming clinical research. However, utilising data to generate new treatments and therapies has continued to prove complicated. The silo-based information systems built over the last 30 years are simply unable to scale to support today’s use cases.
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2. 2 Dental Informatics
Searching Dental E Sources- EM Al-Madi Oct-2012
3. Outline
3
Dental Informatics:
Definition
The Discipline of Dental Informatics
The Scope of Dental Informatics
Dental Informatics Applications
Searching Dental E Sources- EM Al-Madi Oct-2012
4. 4 Definition of Dental informatics
Section 1
Searching Dental E Sources- EM Al-Madi Oct-2012
5. Dental Informatics
Dental informatics is the application of
computer and information science to improve
dental practice, research, education and
management.
A sub-discipline of biomedical informatics
Eisner J. The future of dental informatics. Eur J
Dent Educ. 1999;3(suppl 1):61-9.
Searching Dental E Sources- EM Al-Madi Oct-2012 5
6. 6
The Discipline of Dental
Informatics
Section 2
Searching Dental E Sources- EM Al-Madi Oct-2012
7. Characteristics of a discipline
1. Core of people who conduct research and publish in the
discipline;
Since 1965 approx 3500 authors -2200 articles related to DI and
computer applications in dentistry in 420 journals and
conferences
2. An identifiable body of literature;
Articles in dental journals. J Comp Dentistry. Books; Dental
Informatics by Zimmerman in 1992, The global village of
dentistry, and Imaging in esthetic dentistry.
3. Professional societies and related activities;
Sections within AMIA, IMIA, ADEA, ect
4. Educational programs leading to certificate and advanced
degrees;
General MI degrees with specialization in DI. Joint Degrees.
5. Funded research Programs;
Available as 3rd party funds.cornerstone of T. and H. SPALLEK (2001). Assoc 132: 605-613.
Limited. dental practice." J Am Dent "Dental informatics A
SCHLEYER,
Searching Dental E Sources- EM Al-Madi Oct-2012 7
8. A research discipline;
Not mere application of
computers(≠IT).
Dental Informatics Information Technology
DI= IT =
Development +evaluation of Hardware and software devices to
information models and computing retrieve and display information
applications
DI = IT Technologies =
research and application in software design
conceptualization + development
+organization +creation of I & O devices.
+relevance
+ utilization of information
Searching Dental E Sources- EM Al-Madi Oct-2012 8
9. 9
Inter-related
Innovations =
Computer programs or
devices = (IT).
DI technology
Incorporate DI in the
technology.
Searching Dental E Sources- EM Al-Madi Oct-2012
10. 10 Scope of Dental Informatics
Section 3
Searching Dental E Sources- EM Al-Madi Oct-2012
11. 11
Cognitive science:
is a research area that draws on
several fields (such as
psychology, artificial intelligence,
linguistics, and philosophy) to
develop theories of perception,
thinking, and learning.
Cognitive science relates to
information science as we try to
understand how information is
represented in the human mind.
Computer science relates to
information science as try to
simulate our mental processes in
computing environments.
Biomedicine is replete with
complex cognitive processes
(such as diagnosis, treatment Schleyer, T. K. (2003). "Dental Informatics: An Emerging
planning, and evaluation). Biomedical Informatics Discipline." Adv Dent Res 17:4-8,
December, 2003 17: 4-8.
Searching Dental E Sources- EM Al-Madi Oct-2012
12. 12
Computer science:
is a discipline that
involves the
understanding and
design of computers
and computational
processes. Here, the
emphasis is not on
information, but how it
is represented,
processed, Schleyer, T. K. (2003). "Dental Informatics: An Emerging
Biomedical Informatics Discipline." Adv Dent Res 17:4-
manipulated, and E Sources- EM Al-Madi Oct-20128, December, 2003 17: 4-8.
Searching Dental
managed in
13. 13
Information Science:
is the collection,
classification,
storage, retrieval, and
dissemination of
recorded knowledge
treated both as a
pure and as an
applied science.
Schleyer, T. K. (2003). "Dental Informatics: An Emerging
Biomedical Informatics Discipline." Adv Dent Res 17:4-8,
December, 2003 17: 4-8.
Searching Dental E Sources- EM Al-Madi Oct-2012
14. 14
Telecommunications:
Is the science that deals
with communication at a
distance.
Transmission of digital
images efficiently resulted in
new approaches to image
compression and
transmission.
Another example is
aggregating information
from many different sources,
such as information about
Schleyer, T. K. (2003). "Dental Informatics: An Emerging
the same patient from Biomedical Informatics Discipline." Adv Dent Res 17:4-8,
different healthcare Dental E Sources- EM Al-Madi Oct-2012 December, 2003 17: 4-8.
Searching
providers.
15. 15 Dental Informatics Applications
Section 4
Searching Dental E Sources- EM Al-Madi Oct-2012
16. Dental Informatics Applications
Administrative Clinical Educational Research
16 •Practice Management •Electronic Oral health records •Preclinical •Database
•Medical Dental (EOHR) •Haptic feedback •Registries
interface • simulation training
•Computerized billing •Manufacturing •Bibliographic •Terminology and
•Insurance form •Video lib nomenclature
generation and claims standards
processing •Voice Recognition
•Labs •Intra-oral cameras and imaging •Patient education & •Patient Risk
•E-prescribing •3-D image modeler &Diagnostic decision aids Profiling &
predictive modeling assesment
•Pre visit preparation •Radiography •Web Portal & blogs •Outcomes
•Alerts and reminders •Digital radiography Databases
•Secure messaging •Intelligent time series
•Recall tracking comparative X-ray analysis
•Patient registration and •Decision support •Nano-robotics
scheduling •Evidence-based Treatment
•After visit summaries Planning
•Connectivity to patients
•Online ongoing care
relationship
•Tele-consultation &E Sources- EM Al-Madi
Searching Dental referral Oct-2012
17. Fields of DI Research
Informatics Applications
17 Basic Research Office Applications
Challenges Infrastructure
EDR, Outcomes
Coding, data
Vocabularies, Distributed medical Predictor,
structures, high
Clinical automated retrieval records, clinical Treatment Planner,
performance
from repositories trials, teledentistry Clinical Decision
computing
Support Tool
3-D modeler, X-Ray
analyzer, dynamic
3-D modeling, Ontology-based 3-D anatomy
neuromuscular
Imaging visualization, data reference models and atlases, radiological
occlusal simulation,
representation classification diagnosis
Haptic feedback
simulation
Biometric nano-
Biochips, algorithms Linking genomic and Genetic-based
robotics, bioassay
Bioinformatics for DNA sequencing, patient data, security, patient records and
caries/periodontal
patient specific drugs ethics protocols
analyzer
Data mining,
Databases, Integration and
citizen-based
Public/ searching, data validation of Blogs, web portals,
services, social
Population analysis theories and information, PHR,
networks shared
algorithms knowledge discovery
knowledge-base
Searching Dental E Sources- EM Al-Madi Oct-2012
18. 18
Applications in Clinical
Dentistry
Searching Dental E Sources- EM Al-Madi Oct-2012
19. Electronic Oral Health Record
19
EMR EOHR
Reimbursement Dental reimbursement:
Diagnosis codes (ICD-9) & Procedure codes only.
procedure codes (CPT 4). Documentation :
Documentation : Location Finding
Graphics, templates
Finding Location
Sequence
Text
Holistic
Treatment:
Procedure implies
Treatment: pathology present.
Roadmap for patient to Roadmap for dentist
follow Searching Dental E Sources- EM Al-Madi Oct-2012
20. 20 Searching Dental E Sources- EM Al-Madi Oct-2012
21. 21 Searching Dental E Sources- EM Al-Madi Oct-2012
22. Endodontics
22
Digital radiography refers
to a method of capturing a
radiographic image using a
sensor, breaking it into an
electronic pieces, and
presenting and storing the
image using a computer.
The sensor receives the
analog information and
converter (ADC) to
converts it to a digital
image Digital Radiography
The image is displayed
within seconds or minutes
on the computer screen in
front of the clinician and
the patient/client.
Searching Dental E Sources- EM Al-Madi Oct-2012
23. Viewbox is advanced software for cephalometric analysis. It is used in
Orthodontic Departments around the world. Viewbox can be customized to
almost any task. Points, measurements and analyses are not 'hard-wired',
enabling you to go beyond the confines of cephalometric radiographs and
perform measurements on any kind of radiograph, photograph or other two-
dimensional or 3-D image. Furthermore, sophisticated algorithms are included
23 for image enhancement, facilitation of point Al-Madi Oct-2012 morphometric
Searching Dental E Sources- EM identification and
analys
24. 3-D Scanning & Milling
24
Many Chairside dental
CAD/CAM systems and
Dental Laboratory CAD/CAM
systems use 3D Scanner
technologies to capture the
3D surface of a dental
preparation (either in vivo or
in vitro), in order to produce a
restoration digitally using
CAD software and ultimately
produce the final restoration
using a CAM technology
(such as a CNC milling
machine, or 3D printer). The
chairside systems are
designed to facilitate the 3D
scanning of a preparation in
vivo and produce the
restoration (such as a Crown,
Onlay, Inlay or Veneer). Dental E Sources- EM Al-Madi
Searching Oct-2012
25. Image-guided dental
25
implantology
It provides a full 3D view of
the patient’s anatomy, as a
basis for evaluation and
functional and aesthetic
implant planning.
Accurate examination of
bone, muscles and other
tissues by switching
among them in real-time
Its high image definition
facilitates the observation
of the anatomical
structures, allowing proper
and secure planning and
reducing all uncertainties
during surgery.
Searching Dental E Sources- EM Al-Madi Oct-2012
26. 3D-Time Series Analysis
Time series analysis stands for comparing image
data sets from the same person or specimen
taken at different times to show the changes.
Image segmentation, rigid registration and a voxel
based non-rigid registration as well as 3D
visualization, allows a time series analysis based
on DICOM CT images.
In dentistry the scope of further application ranges
from pre- and postoperative oral surgery images
(orthognathic surgery, trauma surgery) to
endodontic and orthodontic treatment.
Searching Dental E Sources- EM Al-Madi Oct-2012 26
27. Teledentistry
27
Conditions that only visual using the Internet to
inspection or history is consult with an expert.
needed for interpretation This consultation could
Oral medicine be:
Chronic Facial Pain direct (between the
patient and the expert)
Assisting patients with
concerns: indirect (between the
patient‟s doctor and the
Trauma expert).
Finding a dentist Phone call to expert
Specific organizations with Fax charts and records
urban and rural centers:
Internet: scanned image,
MOH, KFSH, MOD, ect digital image, and audio
transfer of requests
Searching Dental E Sources- EM Al-Madi Oct-2012
28. InteractiveMD is a telehealth company that
connects patients with doctors via real-time
videoconferencing, phone, and secure email,
MDLiveCare is an on-demand telehealth
company that provides patients with remote
access via video, phone, and secure email to
board certified doctors and licensed therapists.
Virtual Hospitals of the future??
Searching Dental E Sources- EM Al-Madi Oct-2012 28
29. Teledentistry in Use:
http://www.urmc.rochester.edu/news/story/index.cfm?id=1774
Searching Dental E Sources- EM Al-Madi Oct-2012 29
30. 30
Applications in Dental
education
Searching Dental E Sources- EM Al-Madi Oct-2012
31. Virtual Patients
31
The Virtual Dental Patient (VDP) application
was designed to aid dentists in getting
acquainted with the teeth anatomy, the
handling of drilling instruments and the
challenges associated with the drilling
procedure.
The VDP simulator allows the user to :
view/manipulate a 3-D head and oral cavity
model constructed using anatomical data,
adapt the model to the characteristics of
specific patient using either facial photographs
or 3D data,
animate it using an MPEG-compatible facial
animation player and
perform virtual tooth drilling within the oral
cavity using a Phantom haptic device to
control the drilling tool.
Drilling is performed on 3D
volumetric/surface models of teeth, obtained
from cross sections of real teeth.
Model adaptation using two facial
Searching Dental E Sources- EM Al-Madi Oct-2012
photographs
32. Manikin-based simulators
32
DentSim™, consists of a
manikin with head and
dentoform (plastic teeth), a
dental hand-piece and a light,
an infrared camera and two
computers. The manikin head
and the hand-piece contain
infrared emitters that are
tracked by the infrared
camera. Using this optical
tracking system to trace the
movements of a hand piece,
the simulator scores the
accuracy of a student's cavity
preparation in a manikin’s
synthetic tooth.
Searching Dental E Sources- EM Al-Madi Oct-2012
33. 33 Searching Dental E Sources- EM Al-Madi Oct-2012
34. Image guidance simulators
34
Image Guided Implantology
(IGI), for teaching, diagnosis,
treatment planning and
placement of implants.
Providing a particular
patient’s CAT scan, the
simulator allows the patient
and the virtual model image
to be coordinated during the
actual surgery. If the
computer recognizes that the
surgeon is making a serious
deviation from the treatment
plan during the actual
surgery, the computer will
stop the hand-piece and the
surgeon will need to override
the computer to continue.
Searching Dental E Sources- EM Al-Madi Oct-2012
35. Haptic Devices
35
Virtual Reality Dental Training System
(VRDTS).
Aiming for cavity preparation, the software
simulates a set of dental instruments.
Using VRDTS dental students work with a
virtual decayed tooth and learn to probe it for
diagnosis, use a drill to prepare a tooth for
cavity repair, fill the prepared cavity with
amalgam and carve the amalgam to match
the original tooth contour. Unlike plastic
teeth, VRDTS enables the student to feel the
difference between enamel, dentin, caries,
amalgam and pulp throughout the
procedure.
The student's operation can be tracked
precisely in real time, providing quantifiable
feedback to both student and teacher.
Lastly, since the entire process is virtual, the
student has the ability to zoom, rotate and
even cut the tooth in cross section to better
understand the process. VRDTS offers the
student the opportunity to practice
procedures as often as needed, with no
additional cost for materials.
Searching Dental E Sources- EM Al-Madi Oct-2012
36. Haptic Devices
36
PerioSim Force Feedback Dental
Simulator
Students guide a stylus on-screen that
resembles an explorer They can feel life-like
tactile sensations as they navigate through
various procedures.
Students can access PerioSim via the
Internet. A realistic 3-D human mouth is
shown in real-time, and the user can adjust
the model position, viewpoint and
transparency level.
The system allows instructors to create short
scenarios of periodontal procedures, which
can be saved and replayed at any time. The
3-D component permits students to replay
from any angle, so the user can observe
different views of the placement of the
instrument and gingival relationships during
a procedure, Steinberg said.
The recorded file is an actual representation
of the original scenario, which offers great
training potential.
The program also allows for a second
playback mode, where an instructor leadsE Sources- EM Al-Madi
Searching Dental Oct-2012
the trainee through the program. By simply
holding onto the haptic stylus, the trainee
37. 37 General & Patient Education
Searching Dental E Sources- EM Al-Madi Oct-2012
38. 38 Searching Dental E Sources- EM Al-Madi Oct-2012
39. 39 Searching Dental E Sources- EM Al-Madi Oct-2012
41. Information types
41
Knowledge:
Literature
Clinical trials
Clinical learning
Patient information
Demographic
information
Patient history
Clinical examination
Searching Dental E Sources- EM Al-Madi Oct-2012
42. Information needs
(Gorman 1995)
42
Unrecognized need
Clinician
is unaware of information need or
knowledge deficit
Recognized need
Clinician aware of need but may or may not
pursue it
Pursued need
Information
seeking occurs but may or may not
be successful.
Satisfied need
Information seeking successful.
Searching Dental E Sources- EM Al-Madi Oct-2012
43. 43
Knowledge
Information
Data
Facts
Searching Dental E Sources- EM Al-Madi Oct-2012
44. 44
Create
Evaluate
Analyze
Apply
Understand
Remember
Digital Blooms by Sources- EM Fisher, 2009
Searching Dental E
Mike Al-Madi Oct-2012
45. 45
Although students are presented with massive
amounts of information during their course of study,
more often than not, students graduate with gaps in
their knowledge.
Accessing recent online information is very important to
help clinicians and students answer questions that
might arise during their clinical practice.
Searching Dental E Sources- EM Al-Madi Oct-2012
46. Content of Knowledge based information
resources
46
1. Bibliographic: Literature reference databases, or citations or pointers to
the medical literature. Ex. Medline
Or Web catalogs: Web pages consisting of links to other web pages and
sites. Ex: www.Healthfinder.gov
2. Full text content: Online versions of books and periodicals, and websites
3. Databases/Collections: Information housed in Database management
systems. They can be further categorized into information types:
Image databases
Genomics databases
Citation databases
EBM databases
Other databases
Example: Entrez system: (www.ncbi.nlm.nih.gov/Entrez)
4. Aggregations: Collections of content from the first 3 categories.
Developed for all kinds of users from consumers, to clinicians to
scientists. Ex. Medline plus (www.medlineplus.gov)
Searching Dental E Sources- EM Al-Madi Oct-2012
47. Differences between Traditional
and Digital Libraries
47
Traditional Libraries Digital libraries
Acquisition and maintenance of collections Acquisition and maintenance of collections
Cataloging and classification of items in Cataloging and classification of items in
collection to make them more accessible to collection to make them more accessible to
users. users.
Serving as a place where individuals can go to Seeking of information online can be easier or
seek information with assistance, including harder (depending on level of computer skills,
information on computers. searching skill and distractions)
Providing work or studying space (particularly No limitation on space to work can be an
in universities). advantage and disadvantage.
Information in multiple copies (replaceable) Although multiple users can access at once.
Copies are constantly changing
Less worry about Quality of publications Internet publishing may not always be quality
Items are static (easier cataloging and stable Cataloging is more difficult due to changing
archiving) nature, and access to entire journal is lost when
subscription is terminated.
Searching Dental E Sources- EM Al-Madi Oct-2012
48. Issues with digital libraries
48
Access:
Digital libraries must ensure documents have
persistent identifiers (URL), so that if the document
moves, it is still obtainable.
Interoperability:
Ensure that resources with heterogeneous metadata
can be accessed.
Intellectual property:
Establishment of who owns the information.
Preservation:
Life expectancy of Storage material type and longevity
Changes in technology of storage media
Searching Dental E Sources- EM Al-Madi Oct-2012
49. 49 Search strategies
Have you ever had some
difficulties searching for
information using the
internet ??
Searching Dental E Sources- EM Al-Madi Oct-2012
50. Planning for Your Search
50
Determine your GOAL from search:
Pao’s 4 stages of search (Information Need, Question,
Request) How to translate that into clinical/research
needs.
Determine the SCOPE of the search:
Decide on the comprehensiveness of answer, and level
of evidence needed (RCT, systemic review, case
report?).
Identify the KEY WORDS or concepts:
From previous articles, or alternative expressions
Determine the DATABASE you need
to search in (General, Organization, Journal, ect)
Searching Dental E Sources- EM Al-Madi Oct-2012
51. Background info
51
General Search
Google
Wikipedia
Google Books
Youtube
Searching Dental E Sources- EM Al-Madi Oct-2012
52. General Search is good for
52
finding…
Introductions
Basic Definitions
Location of Reliable information
List of references
Numerical data
Searching Dental E Sources- EM Al-Madi Oct-2012
53. Search Strategies and Tips 1
53
Using „AND‟ narrows a search: results must include
both terms, e.g.:
Dental AND “Online Information”
Using „OR‟ broadens a search: results can include
either term, e.g.:
Planning OR Management
Benefits OR Strengths OR Advantages
Dental OR “Online information”
Searching Dental E Sources- EM Al-Madi Oct-2012
54. Search Strategies and Tips 2
54
Using „NOT‟ specifies a term must not appear in the
results, e.g.:
Cancer NOT oral
When searching for phrases, enclose using: “….. ” ,
e.g.:
“ Lung Cancer”
“ Behavioral Economics ”
Searching Dental E Sources- EM Al-Madi Oct-2012
55. Search Strategies and Tips 3
55
Think before you start – concept map / brain storm
Start with the catalogue – database – internet (or at least
use all of the tools)
Develop a search strategy and be prepared to change it!
Record all the details of all your references as you go
You will need this information for your in text citations
and reference lists
Remember one useful book / article leads to others
References (back in time)
Cited By (forward in time)
Searching Dental E Sources- EM Al-Madi Oct-2012
56. Too much or too little?
56
Too Much Information Not enough information
Is your topic too Is your search too
broad? specific?
Narrow your topic Check your spelling!
using more specific Use TRUNCATION and
terms OR operators
Use AND, NOT Are you looking in the
Use date limiters / right place
search limiters Maybe there isn‟t
much on the topic
Searching Dental E Sources- EM Al-Madi Oct-2012
57. 57
Dental e-Resources
Searching Dental E Sources- EM Al-Madi Oct-2012
58. 58
Google
www.google.com
Searching Dental E Sources- EM Al-Madi Oct-2012
59. Getting started
59
Type a keyword into the basic search box or
click on “Advanced search” for more searching
options
Searching Dental E Sources- EM Al-Madi Oct-2012
60. Advanced search
60
Enter keywords into the various advanced
search fields to narrow the result
Searching Dental E Sources- EM Al-Madi Oct-2012
61. Advanced search
61
Limit your research to a specific author,
publication or a time period
Searching Dental E Sources- EM Al-Madi Oct-2012
62. Advanced search
62
Find more relevant information by limiting
result to a specific field of a study
Searching Dental E Sources- EM Al-Madi Oct-2012
63. Search Result
63
Find other paper similar to search result by
clicking on the “Related Articles” link
Searching Dental E Sources- EM Al-Madi Oct-2012
64. 64
PubMed
http://www.ncbi.nlm.nih.gov/sites/entrez?db=PubMed
Searching Dental E Sources- EM Al-Madi Oct-2012
65. Pubmed-Main page
http://pubmed.gov
65
Searching Dental E Sources- EM Al-Madi Oct-2012
66. Searching
66
1. Type a word or phrase into the query box, including
subject, author and/or journal.
2. Combine search terms with connector words:
“AND”, “OR” or “NOT” using upper case letters.
3. Use * at the end of the word (e.g., mimic*) if you
want to search for different endings of mimic,
mimicking, mimics, etc.
Searching Dental E Sources- EM Al-Madi Oct-2012
67. Results list
67
Searching Dental E Sources- EM Al-Madi Oct-2012
68. Accessing Full-Text
Many PubMed citations have links to the full-
68
text of articles through PubMed Central
Searching Dental E Sources- EM Al-Madi Oct-2012
69. 69
King Saud University
Library
ScienceDirect
Scopus – Elsevier
Blackwell Synergy
Searching Dental E Sources- EM Al-Madi Oct-2012
70. 70 Open-Access Journals
The Open Dentistry Journal
BMC Oral Health
Dental Research Journal
The Brazilian Dental Journal
The Internet Journal of Dental Science
Contemporary Clinical Dentistry
Saudi Dental Journal
Directory of open access journals
Searching Dental E Sources- EM Al-Madi Oct-2012
71. 71
Dental Societies
Saudi Dental Society
American Dental Association
Searching Dental E Sources- EM Al-Madi Oct-2012
73. 73 Reference Managers
Searching Dental E Sources- EM Al-Madi Oct-2012
74. Reference Managers
74
Reference management software, citation
management software or personal
bibliographic management software is
software for scholars and authors to use for
recording and utilizing bibliographic citations
(references).
Once a citation has been recorded, it can be
used time and again in generating
bibliographies, such as lists of references in
scholarly books, articles and essays.
Searching Dental E Sources- EM Al-Madi Oct-2012
75. 75
Reference management software collects a much
smaller database, of the publications that have been
used or are likely to be used by a particular author or
group, and such a database can easily be housed on
an individual's personal computer.
Ex.
Open Source: Aigaion · Bebop · BibDesk · Bibus ·
Connotea · I, Librarian · JabRef · Pybliographer · refbase ·
refdb · Referencer · Wikindx · Zotero · J!Research
Retail: Biblioscape · Bookends · EndNote · Mendeley ·
Papers · ProCite · Reference Manager · RefWorks · Sente
Web Based: Aigaion · Bebop · CiteULike · Connotea ·
GradeGuru Citation Manager · I, Librarian · Mendeley ·
refbase · refdb · BibSonomy · J!Research
Searching Dental E Sources- EM Al-Madi Oct-2012
76. When you come to the end of your rope, tie a knot
76 and hang on.
Franklin D. Roosevelt
ealmadi@ksu.edu.sa
Searching Dental E Sources- EM Al-Madi Oct-2012