: A wealth of data in public health care systems has been collected and meanwhile there are plenty
of new technological improvements which have considerable influence on current data pool. Nevertheless,
important obstacles are challenging to utilize existing clinical data. Enhanced technological improvements lead
patients to search their symptoms and corresponding diagnosis on online resources. In this study, it is aimed to
develop a machine learning model to suit in different availability of users. Most of the current systems allow
people to choose related symptom in web interfaces or Q&A forums. In addition to these applications it is aimed
to implement a new technique which extracts the text-based symptoms and its related parameters such as, severity,
duration, location, cause, accompanied by any other indicators. This study is applicable for patient`s everyday
language statements besides medical expression of symptoms for corresponding symptoms. Extracted terms are
used as an input of the model and analyzed for matching diagnosis where an accuracy of 72.5% has been
accomplished.
Text Extraction Engine to Upgrade Clinical Decision Support Systemjournal ijrtem
New generation technological improvements lead patients to search their symptoms and
corresponding diagnosis on online resources. In this study, it is aimed to develop a machine learning model to
suit in different availability of users. Most of the current systems allow people to choose related symptom in web
interfaces. In addition to these applications it is aimed to implement a new technique which extracts the text-based
symptoms and its related parameters such as, severity, duration, location, cause, accompanied by any other
indicators. This study is applicable for patient`s everyday language statements besides medical expression of
symptoms for corresponding symptoms which is also supporting initial clinical decision system. Extracted terms
are analyzed for matching diagnosis where an accuracy of 90% has been accomplished.
Departmental Information Systems and Management Information Systems in Health...Nawanan Theera-Ampornpunt
Theera-Ampornpunt N. Departmental information systems and management information systems in healthcare organizations. Presented at: Faculty of ICT, Mahidol University; 2012 Feb 8; Bangkok, Thailand.
Text Extraction Engine to Upgrade Clinical Decision Support Systemjournal ijrtem
New generation technological improvements lead patients to search their symptoms and
corresponding diagnosis on online resources. In this study, it is aimed to develop a machine learning model to
suit in different availability of users. Most of the current systems allow people to choose related symptom in web
interfaces. In addition to these applications it is aimed to implement a new technique which extracts the text-based
symptoms and its related parameters such as, severity, duration, location, cause, accompanied by any other
indicators. This study is applicable for patient`s everyday language statements besides medical expression of
symptoms for corresponding symptoms which is also supporting initial clinical decision system. Extracted terms
are analyzed for matching diagnosis where an accuracy of 90% has been accomplished.
Departmental Information Systems and Management Information Systems in Health...Nawanan Theera-Ampornpunt
Theera-Ampornpunt N. Departmental information systems and management information systems in healthcare organizations. Presented at: Faculty of ICT, Mahidol University; 2012 Feb 8; Bangkok, Thailand.
Big Data, CEP and IoT : Redefining Holistic Healthcare Information Systems an...Tauseef Naquishbandi
Healthcare industry has been a significant area for innovative application of various technologies over decades. Being an area of social relevance governmental spending on healthcare have always been on the rise over the years. Event Processing (CEP) has been in use for many years for situational awareness and response generation. Computing technologies have played an important role in improvising several aspects of healthcare. Recently emergent technology paradigms of Big Data, Internet of Things (IoT) and Complex Event Processing (CEP) have the potential not only to deal with pain areas of healthcare domain but also to redefine healthcare offerings. This paper aims to lay the groundwork for a healthcare system which builds upon integration of Big Data, CEP and IoT.
Dr Sanjoy Sanyal wrote this article when he was doing his Masters in Royal College of Surgeons of Edinburgh, University of Bath, United Kingdom.
It traces the origin of the term and discipline called 'Medical Informatics'; describes its evolution and mentions its current healthcare applicability and academic status.
It is fundamental towards understanding today's Information Explosion and its digital implications in all work atmospheres.
Today Dr Sanjoy Sanyal is Professor and Course Director of Neuroscience and FCM-III in Caribbean.
The Case Study of an Early Warning Models for the Telecare Patients in TaiwanIJERA Editor
To propose a practical early warning analysis model for the telecare patients, this study applied data mining
technology as a basis to investigate the classification of patient groups by disease severity and incidence using
data contained in a telecare database regarding the number of a clinic. The ultimate purpose of this study was to
provide a new direction for telecare system planning and developing strategies.
The subject of this case study was a private clinic which is providing telecare system to patients in Taiwan, and
we used three data mining techniques including discriminant analysis, logistic regression and artificial neural
network to construct an early warning analysis model based on several factors such as: Demographic variables,
pathological signals, health management index, diagnosis and treatment records, emergency notification signal.
According the results, the telecare system can build stronger physician-patient relationship in advance through
previously paying attention to patients’ physiological conditions, reminding them to do self-management, even
taking them to the hospital for observation. A comparison of discriminative rates showed that the artificial neural
network model had the highest overall correct classification rate, 85.52%, and thus is a tool worthy of
recommendation
CONCEPTUAL MODEL FOR ELECTRONIC CLINICAL RECORD INFORMATION SYSTEMijistjournal
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 comprehensive study on disease risk predictions in machine learning IJECEIAES
Over recent years, multiple disease risk prediction models have been developed. These models use various patient characteristics to estimate the probability of outcomes over a certain period of time and hold the potential to improve decision making and individualize care. Discovering hidden patterns and interactions from medical databases with growing evaluation of the disease prediction model has become crucial. It needs many trials in traditional clinical findings that could complicate disease prediction. A Comprehensive study on different strategies used to predict disease is conferred in this paper. Applying these techniques to healthcare data, has improvement of risk prediction models to find out the patients who would get benefit from disease management programs to reduce hospital readmission and healthcare cost, but the results of these endeavors have been shifted.
Web based database management to support telemedicine systemijait
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.
Standardization and wider use of Electronic Health records (EHR) creates opportunities for
better understanding patterns of illness and care within and across medical systems. In the healthcare
systems, hidden event signatures allow taking decision for patient’s diagnosis, prognosis, and
management. Temporal history of event codes embedded in patients' records, investigates frequently
occurring sequences of event codes across patients. There is a framework that enables the
representation, retrieval, and mining of high order latent event structure and relationships within
single and multiple event sequences. There is a wealth of hidden information present in the large
databases. Different data mining techniques can be used for retrieving data. A classifier approach for
detection of diabetes is presented in this paper and shows how Naive Bayes can be used for
classification purpose. In this system, medical data is categories into five categories namely low,
average, high and very high and critical, treatment is given as per the predicted category. The system
will predict the class label of unknown sample. Hence two basic functions namely classification
(training) and prediction (testing) will be performed. An algorithm and database used affects the
accuracy of the system. It can answer complex queries for diagnosing diabetes disease and thus assist
healthcare practitioners to make intelligent clinical decisions which traditional decision support
systems cannot.Over the last decade, so many information visualization techniques have been
developed to support the exploration of large data sets. There are various interactive visual data
mining tools available for visual data analysis. It is possible to perform clinical assessment for visual
interactive knowledge discovery in large electronic health record databases. In this paper, we
proposed that it is possible to develop a tool for data visualization for interactive knowledge
discovery.
Text Extraction Engine to Upgrade Clinical Decision Support SystemIJRTEMJOURNAL
New generation technological improvements lead patients to search their symptoms and
corresponding diagnosis on online resources. In this study, it is aimed to develop a machine learning model to
suit in different availability of users. Most of the current systems allow people to choose related symptom in web
interfaces. In addition to these applications it is aimed to implement a new technique which extracts the text-based
symptoms and its related parameters such as, severity, duration, location, cause, accompanied by any other
indicators. This study is applicable for patient`s everyday language statements besides medical expression of
symptoms for corresponding symptoms which is also supporting initial clinical decision system. Extracted terms
are analyzed for matching diagnosis where an accuracy of 90% has been accomplished.
Big Data, CEP and IoT : Redefining Holistic Healthcare Information Systems an...Tauseef Naquishbandi
Healthcare industry has been a significant area for innovative application of various technologies over decades. Being an area of social relevance governmental spending on healthcare have always been on the rise over the years. Event Processing (CEP) has been in use for many years for situational awareness and response generation. Computing technologies have played an important role in improvising several aspects of healthcare. Recently emergent technology paradigms of Big Data, Internet of Things (IoT) and Complex Event Processing (CEP) have the potential not only to deal with pain areas of healthcare domain but also to redefine healthcare offerings. This paper aims to lay the groundwork for a healthcare system which builds upon integration of Big Data, CEP and IoT.
Dr Sanjoy Sanyal wrote this article when he was doing his Masters in Royal College of Surgeons of Edinburgh, University of Bath, United Kingdom.
It traces the origin of the term and discipline called 'Medical Informatics'; describes its evolution and mentions its current healthcare applicability and academic status.
It is fundamental towards understanding today's Information Explosion and its digital implications in all work atmospheres.
Today Dr Sanjoy Sanyal is Professor and Course Director of Neuroscience and FCM-III in Caribbean.
The Case Study of an Early Warning Models for the Telecare Patients in TaiwanIJERA Editor
To propose a practical early warning analysis model for the telecare patients, this study applied data mining
technology as a basis to investigate the classification of patient groups by disease severity and incidence using
data contained in a telecare database regarding the number of a clinic. The ultimate purpose of this study was to
provide a new direction for telecare system planning and developing strategies.
The subject of this case study was a private clinic which is providing telecare system to patients in Taiwan, and
we used three data mining techniques including discriminant analysis, logistic regression and artificial neural
network to construct an early warning analysis model based on several factors such as: Demographic variables,
pathological signals, health management index, diagnosis and treatment records, emergency notification signal.
According the results, the telecare system can build stronger physician-patient relationship in advance through
previously paying attention to patients’ physiological conditions, reminding them to do self-management, even
taking them to the hospital for observation. A comparison of discriminative rates showed that the artificial neural
network model had the highest overall correct classification rate, 85.52%, and thus is a tool worthy of
recommendation
CONCEPTUAL MODEL FOR ELECTRONIC CLINICAL RECORD INFORMATION SYSTEMijistjournal
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 comprehensive study on disease risk predictions in machine learning IJECEIAES
Over recent years, multiple disease risk prediction models have been developed. These models use various patient characteristics to estimate the probability of outcomes over a certain period of time and hold the potential to improve decision making and individualize care. Discovering hidden patterns and interactions from medical databases with growing evaluation of the disease prediction model has become crucial. It needs many trials in traditional clinical findings that could complicate disease prediction. A Comprehensive study on different strategies used to predict disease is conferred in this paper. Applying these techniques to healthcare data, has improvement of risk prediction models to find out the patients who would get benefit from disease management programs to reduce hospital readmission and healthcare cost, but the results of these endeavors have been shifted.
Web based database management to support telemedicine systemijait
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.
Standardization and wider use of Electronic Health records (EHR) creates opportunities for
better understanding patterns of illness and care within and across medical systems. In the healthcare
systems, hidden event signatures allow taking decision for patient’s diagnosis, prognosis, and
management. Temporal history of event codes embedded in patients' records, investigates frequently
occurring sequences of event codes across patients. There is a framework that enables the
representation, retrieval, and mining of high order latent event structure and relationships within
single and multiple event sequences. There is a wealth of hidden information present in the large
databases. Different data mining techniques can be used for retrieving data. A classifier approach for
detection of diabetes is presented in this paper and shows how Naive Bayes can be used for
classification purpose. In this system, medical data is categories into five categories namely low,
average, high and very high and critical, treatment is given as per the predicted category. The system
will predict the class label of unknown sample. Hence two basic functions namely classification
(training) and prediction (testing) will be performed. An algorithm and database used affects the
accuracy of the system. It can answer complex queries for diagnosing diabetes disease and thus assist
healthcare practitioners to make intelligent clinical decisions which traditional decision support
systems cannot.Over the last decade, so many information visualization techniques have been
developed to support the exploration of large data sets. There are various interactive visual data
mining tools available for visual data analysis. It is possible to perform clinical assessment for visual
interactive knowledge discovery in large electronic health record databases. In this paper, we
proposed that it is possible to develop a tool for data visualization for interactive knowledge
discovery.
Text Extraction Engine to Upgrade Clinical Decision Support SystemIJRTEMJOURNAL
New generation technological improvements lead patients to search their symptoms and
corresponding diagnosis on online resources. In this study, it is aimed to develop a machine learning model to
suit in different availability of users. Most of the current systems allow people to choose related symptom in web
interfaces. In addition to these applications it is aimed to implement a new technique which extracts the text-based
symptoms and its related parameters such as, severity, duration, location, cause, accompanied by any other
indicators. This study is applicable for patient`s everyday language statements besides medical expression of
symptoms for corresponding symptoms which is also supporting initial clinical decision system. Extracted terms
are analyzed for matching diagnosis where an accuracy of 90% has been accomplished.
Big data approaches to healthcare systemsShubham Jain
The idea behind this presentation is to explore how big data will revolutionize existing healthcare system effectively by reducing healthcare concerns such as the selection of appropriate treatment paths, quality of healthcare systems and so on. Large amount of unstructured data is available in various organizations (payers, providers, pharmaceuticals). We will discuss all the intricacies involved in massive datasets of healthcare systems and how combination of VPH technologies and big data resulted into some mind-boggling consequences. Major opportunities in healthcare includes the integration of various data pools such as clinical data, pharmaceutical R&D data and patient behaviour and sentiment data. Finding potential insights from big data with the help of medical image processing techniques, predictive modelling etc. will eventually help us to leverage the ever-increasing costs of care, help providers practice more effective medicine, empower patients and caregivers, support fitness and preventive self-care, and to dream about more personalized medicine.
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
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
The Remote Monitoring System
Michelle L. Wallace
Sentara College of Health Sciences
Pro Phillips
The Remote Monitoring System
Internationally, patient care facilities and healthcare systems are steadily executing organizations that record the patient health in the home setting. The patient avoids unnecessary doctors’ visits, hospital stays and visits to emergency care department (Emani, 2017). Healthcare is providing your patient the best quality of life possible. Concerning individuals particularly patients with heart failure problems, remote monitoring plays a major role in the being afforded to live somewhat of a normal life. Also, with the increase in the baby boomer generation attaining retirement age, there is high demand for the availability of enough and quality home health care (McGonigle & Mastrian, 2017). Unfortunately, heart failure affects many people in the United States. Subsequently, the incidence and prevalence are increasing even with the option of heart failure therapy. The admission of a patient with heart failure is trending daily. Sadly, this effects the elderly more than any other population. The consequence of heart failure is increased instances of disease and or death. Increased debt is also a precipitating factor of heart failure, due to an influx of necessary treatment. To decrease the instances of the over population in the acute care setting, meanwhile eliminating the significant load of substantial cost to the patient, healthcare facilities have implemented the remote monitoring systems.
Promoting the remote health monitoring is one of the most prevalent factors, that provides more enough outcomes for the heart failure patient. Remote patient monitoring can improve patient results by improving to their responsiveness in the instances of emergency. Remote patient monitoring intensifies medical specialists to assist in following the patient biometric real-time and offer solutions immediately (Emani, 2017). Remote patient monitoring boosts suitable escalation mainly with the nervous patients who are very responsive. By surging quickly, the patient may suffer large medical bills that may negatively impact their quality of life. Furthermore, taking responsibility in monitoring is vital in adequately ensuring the patient has soaring results. Appropriate medication is an essential part of treatment regimens, though it is challenging to understand with certainty if the patient id complying with the prescription (Emani, 2017). The remote health monitoring system is arranged to give patients a reminder on the appropriate time to take their medicines. This system also alerts the physician, if the patient isn’t compliant with treatment.
While the remote patient monitoring is designed for patients with heart problems, this system is key in accessing health care services, appropriate care, and regulation, the program must meet a certain legal and regulatory compliance especially with the privacy and data security.
Electronic Health Records: : An electronic health record (EHR) system is now a standard method of using information technology within the healthcare industry. Smaller clinics and practices that continue to use paper systems need to seriously consider investing in this technology
Disease Prediction Using Machine Learning Over Big DataCSEIJJournal
Due to big data progress in biomedical and healthcare communities, accurate study of medical data
benefits early disease recognition, patient care and community services. When the quality of medical data
is incomplete the exactness of study is reduced. Moreover, different regions exhibit unique appearances of
certain regional diseases, which may results in weakening the prediction of disease outbreaks. In the
proposed system, it provides machine learning algorithms for effective prediction of various disease
occurrences in disease-frequent societies. It experiment the altered estimate models over real-life hospital
data collected. To overcome the difficulty of incomplete data, it use a latent factor model to rebuild the
missing data. It experiment on a regional chronic illness of cerebral infarction. Using structured and
unstructured data from hospital it use Machine Learning Decision Tree algorithm and Map Reduce
algorithm. To the best of our knowledge in the area of medical big data analytics none of the existing work
focused on both data types. Compared to several typical estimate algorithms, the calculation exactness of
our proposed algorithm reaches 94.8% with a convergence speed which is faster than that of the CNN-
based unimodal disease risk prediction (CNN-UDRP) algorithm.
Disease Prediction Using Machine Learning Over Big DataCSEIJJournal
Due to big data progress in biomedical and healthcare communities, accurate study of medical data
benefits early disease recognition, patient care and community services. When the quality of medical data
is incomplete the exactness of study is reduced. Moreover, different regions exhibit unique appearances of
certain regional diseases, which may results in weakening the prediction of disease outbreaks. In the
proposed system, it provides machine learning algorithms for effective prediction of various disease
occurrences in disease-frequent societies. It experiment the altered estimate models over real-life hospital
data collected. To overcome the difficulty of incomplete data, it use a latent factor model to rebuild the
missing data. It experiment on a regional chronic illness of cerebral infarction. Using structured and
unstructured data from hospital it use Machine Learning Decision Tree algorithm and Map Reduce
algorithm. To the best of our knowledge in the area of medical big data analytics none of the existing work
focused on both data types. Compared to several typical estimate algorithms, the calculation exactness of
our proposed algorithm reaches 94.8% with a convergence speed which is faster than that of the CNN-
based unimodal disease risk prediction (CNN-UDRP) algorithm.
DISEASE PREDICTION USING MACHINE LEARNING OVER BIG DATAcseij
Due to big data progress in biomedical and healthcare communities, accurate study of medical data
benefits early disease recognition, patient care and community services. When the quality of medical data
is incomplete the exactness of study is reduced. Moreover, different regions exhibit unique appearances of
certain regional diseases, which may results in weakening the prediction of disease outbreaks. In the
proposed system, it provides machine learning algorithms for effective prediction of various disease
occurrences in disease-frequent societies. It experiment the altered estimate models over real-life hospital
data collected. To overcome the difficulty of incomplete data, it use a latent factor model to rebuild the
missing data. It experiment on a regional chronic illness of cerebral infarction. Using structured and
unstructured data from hospital it use Machine Learning Decision Tree algorithm and Map Reduce
algorithm. To the best of our knowledge in the area of medical big data analytics none of the existing work
focused on both data types. Compared to several typical estimate algorithms, the calculation exactness of
our proposed algorithm reaches 94.8% with a convergence speed which is faster than that of the CNNbased
unimodal disease risk prediction (CNN-UDRP) algorithm.
The effect of functionalized carbon nanotubes on thermalmechanical performanc...journal ijrtem
The new approaches for preparing nanocomposite coating by modificated carbon nanonotubes
(CNTs) and epoxy resin was done in the study. thermal-mechanical performance of nanocomposite coating was
investigated and the results were reported in this paper. The physic-chemical techniques such as Differential
scanning calorimetry (DSC) and Thermal gravimetric analysis (TGA) were used to characterize the thermal
performance of Epoxy nanocomposite coating. The test techniques for mechanical properties of paint coating as
adhesion, hardness, impact resistance and bending strength were employed in the work. The results indicated
that CNTs were dispersed in epoxy coating with only ratio of 0.1 wt% enhanced the Glass Transition
Temperature (Tg), decomposition temperature of epoxy coating and improved mechanical properties
significantly. Also functionalized CNTs can be reinforced thermal-mechanical of the epoxy coating better than
neat CNTs.
Development Issues and Problems of Selected Agency in Sorsogon, An investigat...journal ijrtem
: The study venture on the developing issues and problems of selected agency in the province of
Sorsogon with an end-view of identifying solution towards achieving effective delivery of services to the
public. The agencies covered by the study are the employers of the students enrolled in Public Administration
512 subject in the graduate school program of the Sorsogon State College 1st semester SY 2016. Guided by a
structured matrix questionnaire and checklist, the class spearheaded by the assigned focal person per
identified respondent-agency conducted a focus group discussion covering sequentially the issues and
problems besetting the organization. It likewise pursued how does it affects the management & performance of
the office and ultimately identifying possible solutions out of the issues and problems. Result revealed that
most pressing problems and issues of the selected agency in the province of Sorsogon covers; (a) understaffed,
(b) poor communication, (c) poor implementation of the policy, and (d) poor performance feedback
mechanism in the system
Positive and negative solutions of a boundary value problem for a fractional ...journal ijrtem
: In this work, we study a boundary value problem for a fractional
q, -difference equation. By
using the monotone iterative technique and lower-upper solution method, we get the existence of positive or
negative solutions under the nonlinear term is local continuity and local monotonicity. The results show that we
can construct two iterative sequences for approximating the solutions
Organic foods refer to products that are grown naturally or produced by methods that comply
with the standards of organic farming. They are not only environmentally friendly, they are also healthy. Many
people believe organic foods are healthier than conventional food. Today, organic foods have become very
popular and everyone wants to know about their benefits. This paper provides a brief introduction on organic
foods and their pros and cons.
Molecular computers are systems in which molecules or macromolecules individually mediate
information processing functions. Molecular computing provides an alternative to computing using silicon
integrated circuits. It aims at developing intelligent computers using biological molecules as computational
devices. It is a promising means of unconventional computation owing to its capability for massive parallelism.
It offers to augment digital computing with biology-like capabilities. This paper provides a brief introduction to
molecular computing.
Industry 4.0 refers to the current trend of automation and deployment of Internet technologies
in manufacturing. This includes using machine-to-machine and Internet of Things (IoT) deployments to help
manufacturers implement increased automation, improved communication and process monitoring. This trend
of Industry 4.0 (sometimes referred to as the 4th Industrial Revolution) affects most processes and people
throughout society. This paper provides a brief introduction to Industry 4.0.
With mounting concerns over the state of our planet, there is continuing demand that chemists
and chemical engineers should develop greener chemical processes and products. In the 1990s, with the
growing awareness of the hazardous impacts of the chemical industry, the green chemistry revolution was
launched by American chemists Paul T. Anastas and John Warner. Green chemistry is the kind of chemistry that
seeks to minimize pollution, conserve energy, and promote environmentally friendly production. This paper
provides a brief introduction to green chemistry
Rural Livelihood and Food Security: Insights from Srilanka Tapu of Sunsari Di...journal ijrtem
Food security is the foremost need of every human society. It is a fundamental right and
government responsibility but still food insecurity is prevalent in rural areas of least developed nations. To cope
with food insecurity, undertaking diverse income generating activities is common as well as key strategy adopted
by rural people. The objective of this study is to assess rural livelihood and food security status of a remote island
named Srilanka Tapu of Sunsari district. A random sampling technique was used to collect primary data from 40
rural household heads using semi-structured questionnaire. Descriptive methods were used for analyzing. The
findings revealed that the food security situation of the Tapu is insecure. Most basic infrastructures and social
services needed for people livelihood such as road, electricity sufficient food availability, education, healthcare,
sanitation, etc. were found to be extremely poor. Most of the households are small scale farmers involving
themselves in diverse livelihood activities which are mostly temporary, low-skilled and low paying. However,
people are fulfilling their food needs at every cost but are highly vulnerable to food insecurity. Also, their lives
security is equally vulnerable because of disastrous Koshi River flooding which occurs every year in the Tapu.
The findings therefore critically suggest that food security of remote and vulnerable human settlements should be
at top priority in policy formulation and implementation level. The study also recommends a need for an in-depth
research for making evidence based policy interventions for improvement of diversify rural livelihood along with
sustainable environment
Augmented Tourism: Definitions and Design Principlesjournal ijrtem
After designing and implementing several iterations of implantations of augmented reality(AR) in
tourism, this paper takes a deep look into design principles and implementation strategies of using AR at
destination tourism settings. The study looks to define augmented tourism from past implementations as well as
several cases uses designed and implemented for tourism. The discussion leads to formation of frameworks and
best practices for AR as well as virtual reality(VR) to be used in tourism settings. Some main affordances include
guest autonomy, customized experiences, visitor data collection and increased electronic word-of-mouth
generation for promotion purposes. Some challenges found include the need for high levels of technology
infrastructure, low adoption rates or ‘buy-in’ rates, high levels of calibration and customization, and the need for
maintenance and support services. Some suggestions are given as to how to leverage the affordances and meet
the challenges to implementing AR for tourism
A study on financial aspect of supply chain management journal ijrtem
The more common approaches used in the SCM consider only the physical logistic operations
and ignore the financial aspects of the supply chain. The main objective to incorporate financial aspects in
supply chain management is to strengthen managerial decisions concerning financial flows in supply chains,
while empirical knowledge about financial supply chain management (FSCM) is in its early stages. This paper
presents a model for FSCM which financial planning in addition to operation planning is decided in it. The
main contribution of this paper is to define two approaches for Financial Supply Chain Management and to
compare them. This financial approaches are: Traditional financial approach and new financial approach.
Traditional financial approach integrates physical goods flows and financial flows. New financial approach
considers in making decisions other financial indicators such as market to book value, liquidity ratios, capital
structure ratios, and return on equity, sales margin, turnover ratios and stock security ratios, among others.
Moreover, the new approach applies the change in equity instead of the traditional approach measures of profit
as the objective function to be maximized in the presented model. To show the attributes of the presented
approaches, the results of the new approach and the traditional approach is compared. The findings indicate
that the traditional approach leads to lower change in equity compared to the financial approach. Also, the
results clearly reveal the better improvement of using the new approach over the traditional approach, and
convince the decision makers to take advantage of the new approach
Existence results for fractional q-differential equations with integral and m...journal ijrtem
This paper concerns a new kind of fractional q-differential equation of arbitrary order by
combining a multi-point boundary condition with an integral boundary condition. By solving the equation which
is equivalent to the problem we are going to investigate, the Green’s functions are obtained. By defining a
continuous operator on a Banach space and taking advantage of the cone theory and some fixed-point theorems,
the existence of multiple positive solutions for the BVPs is proved based on some properties of Green’s functions
and under the circumstance that the continuous functions f satisfy certain hypothesis. Finally, examples are
provided to illustrate the results.
The following Project shows the benefits of a research established into a multi-products
warehouse belongs to an automotive industry supplier. The main goal was applied a tool recognizing the rules
for distribution and material storage. Once the research was completed, the benefits were, the idle times
reduction per hours/week by the two initial processes. The politics for storage assignment and location, propose
a system to improve the space into this areain order to avoid material management and flow issues. It is
important to mention, the system proposed could be applied into warehouses with storage size and space
restricted by sorting area, also different material types, production settings and physical specifications for
which set warehouses with traditional management of distribution without slack, involves lack of materials,
pieces without records, incorrect location assigned, stock error.
Study of desalination processes of seawater from the desalination plant of La...journal ijrtem
: The use of water for food purposes requires excellent physicochemical quality. To contribute to
the control of water quality. Water treated by reverse osmosis is aggressive and demineralize can not be used
directly as a source of drinking water. The objective of this work is to study, physics-chemical analyzes of raw
water, pretreated osmosis and treated (permeate) and produced water (reservoir) at the desalination plant of
seawater Laayoune (SDL), located in southern Morocco. For this, we have followed several qualitative
parameters such as pH, conductivity, turbidity.
Effect of Cash Management on The Financial Performance of Cooperative Banks i...journal ijrtem
This paper analyses the effect of cash management on the financial performance of cooperatives
banks in Rwanda. A descriptive research design was used. The population comprised of 148 employees of ZIGMA
CSS from which a sample of 108 employees was determined using Solvirn and Yemen’s formula. Data was
collected from both primary and secondary sources using questionnaires and document analysis. Data was
presented using frequency tables from which analysis was made. A multi regression analysis was used to analyse
relationship between the variables. The results from the survey revealed that ZIGMA CSS uses various cash
management techniques in the cash management. The results further revealed a strong relationship between cash
management and financial performance of ZIGMA CSS. The study concludes that cash management is a key tool
in the financial management of the banks since cash forms the biggest asset of the bank. Cooperatives banks
should ensure that they develop policies in effective cash management.
Technical expertise on the cause of engine failure of the Mitsubishi Pajero S...journal ijrtem
The article concerns the case of the damage to the Mitsubishi Pajero Sport engine and the
methodology a technical expert applied to identify a direct cause of failure. The engine failure occurred while a
vehicle was being repaired to eliminate air conditioning malfunction and engine overheating. When repairing, it
was necessary to replace a cylinder head and the pistons were checked removing the pully from a crank shaft.
After the repair had been completed and after 16-day vehicle operation, engine timing belts got damaged. To
eliminate this malfunction, damaged belts were replaced. Thirty (30) days after the vehicle had been put into
operation, emergency engine failure occurred, and a technical expert was called upon to assess the quality of the
repairs having been performed. The article describes the procedures and methodology a technical expert applied.
In the conclusion, the findings are stated. To determine the cause, a vehicle was on the car service station
premises, where a technical expert was present and according to his instructions, diagnostic and subsequent
disassembly works have been done. The procedure of evaluating the key characteristics on individual parts, their
display, and the resulting evaluation are described.
Clustering based Time Slot Assignment Protocol for Improving Performance in U...journal ijrtem
Recently, numerous approaches have been proposed for designing medium access control (MAC)
in underwater acoustic networks (UANs). Some of those works tried to adapt MAC protocols proposed for
terrestrial networks. However, unique environmental characteristics of UANs make the MAC protocols hard to be
used in the UANs and degrade network performance. In order to improve network performance, COD-TS MAC
protocol was proposed. COD-TS focuses on both single hop and multi-hop mode and utilizes CDMA for
exchanging schedule information between cluster heads. COD-TS has shortcomings such as collisions, additional
energy consumption by exchanging schedule information and near-far effect of CDMA. To overcome above
shortcomings, we propose a clustering-based time slot assignment protocol. In the proposed protocol, nodes are
clustered, and each cluster head performs two-hop neighbor cluster discovery operation. And then, a cluster head
obtains its own relative position information. Finally, the cluster head assigns its own time slot for data
transmission based on the information. Simulation results show that the proposed protocol has always better
performance compared to the COD-TS.
Design and Implementation of Smart Bell Notification System using IoT journal ijrtem
Smart phones have become part of our daily life. People using smart phones have increased
rapidly. The proposed paper is to provide a security system that combines the functions of smart phone and home
network system. It enables the users to check the image of the visitor who is present at the door. It also saves all
the images in their drive. We send an alert message to the Owner whenever the doorbell is pressed. Furthermore,
the owner can call to the visitor with the help of our app. We are also providing a link in the SMS sent so that it
redirects the user to the app
Assessment of the Water Quality of Lake Sidi Boughaba (Ramsar Site 1980) Keni...journal ijrtem
Sidi Boughaba Lake, part of a wetland complex of Morocco (Ramsar site in 1980) is located on
the Atlantic coast of northwestern Morocco, oriented NNE - SSW and located in an interdunal depression. The
existence of this body of water is due to the fact that the topographic surface is at a lower cost than that of the
piezometric surface of the coastal water table, rainwater and runoff water. The objective of this study is to
determine the physical and chemical characteristics of the waters of this lake. Thus, several water samples were
taken monthly in the period 2016-2017. Parameters such as: temperature, pH, electrical conductivity (EC),
chloride (Cl-
), turbidity (NTU), calcium (Ca2+) and magnesium (Mg2+). The results obtained show that the
distribution of the analyzed elements in Lake waters is quite variable between seasons, as well as between stations.
However, the analysis showed that the studied waters are very mineralized, with an EC between 7 g/l and 14.8
g/l. This mineralization is essentially evaporitic and is controlled by various processes, such as evaporation and
marine influence by aerosol.
The case of a cyclist and tractor traffic accident journal ijrtem
When assessing the cause of a traffic accident, it is also necessary for the technical expert to
take into account the real influences that affect individual participants. This is especially important for accidents
in which one of the participants is cyclist. Technical expert must consider all the circumstances necessary to
assess the cyclist´s behavior. Negligible is not even the age of a cyclist, since in the case of a child or an old man
the driver overtaking bicycle should take this into consideration. The article deals with case of traffic accident
between tractor with the trailer and a bicycle which was riding by cyclist at the age of 80. Apart from the described
procedure by expert in the calculations, the influences on participants' behavior are also discussed
: This paper is aimed at designing a density based dynamic traffic signal system where the timing
of signal will change automatically on sensing the traffic density at any junction using the IoT technology. Traffic
congestion is a severe problem in most cities across the world and therefore it is time to shift more manual mode
or fixed timer mode to an automated system with decision making capabilities. To optimize this problem, we have
made a framework for an intelligent traffic control system. Sometimes higher traffic density at one side of the
junction demands longer green time as compared to standard allotted time. We therefore propose here a
mechanism in which the time period of green light and red light is assigned on the basis of the density of the
traffic present at the time. This is achieved by using LIDAR sensors.
About
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Student information management system project report ii.pdfKamal Acharya
Our project explains about the student management. This project mainly explains the various actions related to student details. This project shows some ease in adding, editing and deleting the student details. It also provides a less time consuming process for viewing, adding, editing and deleting the marks of the students.
Welcome to WIPAC Monthly the magazine brought to you by the LinkedIn Group Water Industry Process Automation & Control.
In this month's edition, along with this month's industry news to celebrate the 13 years since the group was created we have articles including
A case study of the used of Advanced Process Control at the Wastewater Treatment works at Lleida in Spain
A look back on an article on smart wastewater networks in order to see how the industry has measured up in the interim around the adoption of Digital Transformation in the Water Industry.
CFD Simulation of By-pass Flow in a HRSG module by R&R Consult.pptxR&R Consult
CFD analysis is incredibly effective at solving mysteries and improving the performance of complex systems!
Here's a great example: At a large natural gas-fired power plant, where they use waste heat to generate steam and energy, they were puzzled that their boiler wasn't producing as much steam as expected.
R&R and Tetra Engineering Group Inc. were asked to solve the issue with reduced steam production.
An inspection had shown that a significant amount of hot flue gas was bypassing the boiler tubes, where the heat was supposed to be transferred.
R&R Consult conducted a CFD analysis, which revealed that 6.3% of the flue gas was bypassing the boiler tubes without transferring heat. The analysis also showed that the flue gas was instead being directed along the sides of the boiler and between the modules that were supposed to capture the heat. This was the cause of the reduced performance.
Based on our results, Tetra Engineering installed covering plates to reduce the bypass flow. This improved the boiler's performance and increased electricity production.
It is always satisfying when we can help solve complex challenges like this. Do your systems also need a check-up or optimization? Give us a call!
Work done in cooperation with James Malloy and David Moelling from Tetra Engineering.
More examples of our work https://www.r-r-consult.dk/en/cases-en/
Industrial Training at Shahjalal Fertilizer Company Limited (SFCL)MdTanvirMahtab2
This presentation is about the working procedure of Shahjalal Fertilizer Company Limited (SFCL). A Govt. owned Company of Bangladesh Chemical Industries Corporation under Ministry of Industries.
Explore the innovative world of trenchless pipe repair with our comprehensive guide, "The Benefits and Techniques of Trenchless Pipe Repair." This document delves into the modern methods of repairing underground pipes without the need for extensive excavation, highlighting the numerous advantages and the latest techniques used in the industry.
Learn about the cost savings, reduced environmental impact, and minimal disruption associated with trenchless technology. Discover detailed explanations of popular techniques such as pipe bursting, cured-in-place pipe (CIPP) lining, and directional drilling. Understand how these methods can be applied to various types of infrastructure, from residential plumbing to large-scale municipal systems.
Ideal for homeowners, contractors, engineers, and anyone interested in modern plumbing solutions, this guide provides valuable insights into why trenchless pipe repair is becoming the preferred choice for pipe rehabilitation. Stay informed about the latest advancements and best practices in the field.
Hierarchical Digital Twin of a Naval Power SystemKerry Sado
A hierarchical digital twin of a Naval DC power system has been developed and experimentally verified. Similar to other state-of-the-art digital twins, this technology creates a digital replica of the physical system executed in real-time or faster, which can modify hardware controls. However, its advantage stems from distributing computational efforts by utilizing a hierarchical structure composed of lower-level digital twin blocks and a higher-level system digital twin. Each digital twin block is associated with a physical subsystem of the hardware and communicates with a singular system digital twin, which creates a system-level response. By extracting information from each level of the hierarchy, power system controls of the hardware were reconfigured autonomously. This hierarchical digital twin development offers several advantages over other digital twins, particularly in the field of naval power systems. The hierarchical structure allows for greater computational efficiency and scalability while the ability to autonomously reconfigure hardware controls offers increased flexibility and responsiveness. The hierarchical decomposition and models utilized were well aligned with the physical twin, as indicated by the maximum deviations between the developed digital twin hierarchy and the hardware.
E-Symptom Analysis System to Improve Medical Diagnosis and Treatment Recommendation
1. Invention Journal of Research Technology in Engineering & Management (IJRTEM)
ISSN: 2455-3689
www.ijrtem.com Volume 2 Issue 3 ǁ March. 2018 ǁ PP 01-06
| Volume 2 | Issue 3 | www.ijrtem.com | 1 |
E-Symptom Analysis System to Improve Medical Diagnosis and
Treatment Recommendation
Merve Kevser Gökgöl 1
, Zeynep Orhan 2
1,2
Department of Information Technologies, International Burch University, Sarajevo, Bosnia and Herzegovina
ABSTRACT: A wealth of data in public health care systems has been collected and meanwhile there are plenty
of new technological improvements which have considerable influence on current data pool. Nevertheless,
important obstacles are challenging to utilize existing clinical data. Enhanced technological improvements lead
patients to search their symptoms and corresponding diagnosis on online resources. In this study, it is aimed to
develop a machine learning model to suit in different availability of users. Most of the current systems allow
people to choose related symptom in web interfaces or Q&A forums. In addition to these applications it is aimed
to implement a new technique which extracts the text-based symptoms and its related parameters such as, severity,
duration, location, cause, accompanied by any other indicators. This study is applicable for patient`s everyday
language statements besides medical expression of symptoms for corresponding symptoms. Extracted terms are
used as an input of the model and analyzed for matching diagnosis where an accuracy of 72.5% has been
accomplished.
KEYWORDS: Symptom extraction, text matching, medical diagnosis, public healthcare
I. INTRODUCTION
The era of digitization has led computers to become the real face of handling commercial processes across a wealth
of industries. As institutions today specifically in the medical domain have resorted to these virtual machines for
realizing their goals, more and more medical data is being generated on a continuous basis (Davis et al., 2008).
This data is being used in many recommendation systems which deliver a personalized individual's health profile
model (Bolón-Canedo et al., 2015). The quality of health care can be precisely defined and measured with a degree
of scientific accuracy comparable with that of most measures used in clinical medicine (Schiff, 2009). Every year
very large number of population is affected by wrong or late diagnosis (Leape et al., 1991). Diagnoses that are
missed, incorrect or delayed are believed to affect 10 to 20 percent of cases, far exceeding drug errors and surgery
on the wrong patient or body part, both of which have received considerably more attention (Leape et al., 1991).
Current systems are challenging to optimize the utilization of existing medical data resources in automated
diagnostics. With an increased significance on providing better quality and reducing costs, new systems are
required to improve in public healthcare. Clinical decision support systems (CDSS) are computer systems
designed to impact clinical decision making about individual patients at the point in time that these decisions are
made (Kaul, Kaul, & Verma, 2015). It is also important to balance prevention of medical errors while providing
a quick and low-cost health services. CDSS have been a key element of systems’ approaches to improving patient
safety and the quality of care and have been a key requirement for “meaningful use” of electronic health records
(EHRs) (Kaul et al., 2015). The potential for information technology in health care is still in the process of being
actualized. Large dimensionality of data in medicine together with the common reduced sample size of
pathological cases makes indispensable the use of advanced machine learning techniques for clinical interpretation
and analysis (Spyns, Nhàn, Baert, Sager, & De Moor, 1998). The detection and interpretation of pathological
conditions usually required large number of experts available, however the number of experts is sometimes not
enough, and other problems may appear such as disagreement among experts (Spyns et al., 1998).
Information technology (IT) maintains a significant, sustainable knowledge which is vital for organization
development. While the utilization of current data leads services to be more accessible and mobile, it is vital for
health care industry to provide easier and faster accessibility as well as affordable and higher quality of service.
Health IT is not just about merely digitizing medical records to create a paperless office, although doing this will
achieve considerable savings, it is also about fundamentally transforming the health care system so that both
doctors and patients have access to information and tools that allow them to better manage their care (Singh &
Sittig, 2015).
2. E-Symptom Analysis System to Improve…
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II. BACKGROUND
There are a wide range of techniques that can be applied to analyzing these texts, as reflected in the considerable
amount of research in the field of natural language processing (Popowich, 2005) The electronic patient records
contains a rich source of valuable clinical information, which could be used for a wide range of automated
applications aimed at improving the health care process, such as alerting for potential medical errors, generating
a patient problem list, and assessing the severity of a condition (Friedman et al., 2004). However, these
applications are not applicable since large amount of information is in textual form (Tange et al., 1998).
Techniques for automatically encoding textual documents from the medical record have been evaluated by several
groups. Examples are the Linguistic String Project (Xu et al., 2010), and Medical Language Extraction and
Encoding system (Med LEE) (Friedman et al., 2004). Med LEE has been recently adapted to extract Unified
Medical Language System (UMLS) concepts from medical text documents, achieving 83% recall and 89%
precision (Alan R Aronson, 2001).
Figure 1. Overview of components of Med LEE
Figure 1 indicates the components of Med LEE. The knowledge-based components are shown as ovals; the
processing engines are shown as rectangles and the new work discussed in this report involves the final stages of
processing, the encoding process, which occurs after structured output is obtained (Friedman et al., 2004) Other
systems automatically mapping clinical text concepts to a standardized vocabulary have been reported, like Meta
Map (Zou et al., 2003), Index Finder (Pratt et al., 2003), and Knowledge Map (A R Aronson & Rindflesch, 1997).
Meta Map and its Java version called Meta Map Transfer (MM Tx ) were developed by the US National Library
of Medicine (NLM). They are used to index text or to map concepts in the analyzed text with UMLS concepts.
Figure 2. Meta Map sample of processing
A sample Meta Map processing biomedical text and to extract different types of information like anatomical
concepts or molecular binding concepts (Wright et al., 1999) is shown in Figure 2. Meta Map has also been used
with patient’s electronic messages to automatically provide relevant health information to the patients (Meystre
et al., 2008).
3. E-Symptom Analysis System to Improve…
| Volume 2 | Issue 3 | www.ijrtem.com | 3 |
III. METHODOLOGY
In this study, process of data collection allows patients to enter their symptoms by typing in everyday language.
Therefore, to increase the accuracy firstly it is required to clean and eliminate significant words. During this
preprocessing, stop words, vague abbreviations are removed. Each symptom and other data valued words
including severity, duration, location, cause, accompanied by any other symptoms, change in intensity are also
extracted from written expression (as an individual expression or sentence structure of symptoms) accordingly.
The structure of collected data categorized in four main branches; symptoms, diseases, tests (medical
examinations) and corresponding treatments as described in Table 1.
Table 1. General structure of database table
Once tables are created symptoms are analyzed as input and they are trained by the process to detect possible
diagnoses, tests and treatments. Disease data table as indicated in Table 2 consists of ID, Name, Description,
Symptoms ID, Tests ID, Treatments ID, Risks, Causes, Preventions and Complications. Data content of
symptoms, tests and treatments are represented with numerical values in different databases and they are
embedded to system to analyze strength of the relationship.
ID 24
Name Leukemia
Description
Leukemia is cancer of the body's blood-forming tissues, including the bone marrow
and the lymphatic system.
Symptoms ID 21,69,114,119,133,168,173,0,0,0,0,0,0,0,0
Test ID 8,94,104
Treatment ID 113,114,115,116,117
Risks
Factors that may increase your risk of developing some types of leukemia include:
Previous cancer treatment. People who've had certain types of chemotherapy and
radiation therapy for other cancers have an increased risk of developing certain types
of leukemia. Genetic disorders. Genetic abnormalities seem to play a role in the
development of leukemia. Certain genetic disorders, such as Down syndrome, are
associated with an increased risk of leukemia. Exposure to certain chemicals.
Exposure to certain chemicals, such as benzene — which is found in gasoline and is
used by the chemical industry — also is linked to an increased risk of some kinds of
leukemia. Smoking. Smoking cigarettes increases the risk of acute myelogenous
leukemia. Family history of leukemia. If members of your family have been diagnosed
with leukemia, your risk for the disease may be increased'
Causes
Scientists don't understand the exact causes of leukemia. It seems to develop from a
combination of genetic and environmental factors.
Prevention None
Complications None
Gender Not gender restricted
Age Not age restricted
Table 2. Diseases table in database
Symptoms Diseases Tests Treatments
ID ID ID ID
Name Name Name Name
No cation ID Description Definition Definition
Level ID Symptoms ID Why is done
Causes Test ID Preparation
See doctor Treatment ID Expectation
Risks Risks
Causes Results
Prevention
Complications
Gender
Age
4. E-Symptom Analysis System to Improve…
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As shown in Table 3 symptoms are identified by ID value, name, locations (neck, knee, eye, low back), level of
the symptom which is also indicated with numerical values (sharp, low, high, sudden, mild, etc…) and causes,
and possible conditions for a patient to visit the doctor.
ID 3
Name Abdominal pain
Location ID stomachache, tummy ache, gut ache and bellyache
Level ID 49, 9
Causes
Abdominal pain that steadily worsens over time, often accompanied by the
development of other symptoms, is usually serious. Causes of progressive
abdominal pain include: Cancer, Crohn's disease, Enlarged spleen
(splenomegaly), Gallbladder cancer, Hepatitis (liver inflammation), Kidney
cancer, Lead poisoning, Liver cancer, Non-Hodgkin's lymphoma,
Pancreatic cancer, Stomach cancer, Tubo-ovarian abscess (pus-filled pocket
involving a fallopian tube and an ovary), Uremia (buildup of waste products
in your blood).
See doctor
Have someone drive you to urgent care or the emergency room if you have:
Severe pain, Fever, Bloody stools, Persistent nausea and vomiting, Weight
loss, Skin that appears yellow, Severe tenderness when you touch your
abdomen, Swelling of the abdomen.
Table 3. A sample table of symptoms
Table of tests (medical examinations) which is given in Table 4, describes details about essential examinations`
ID, name, definition, why it is required (why is done), preparation, expectation, risks, results.
ID 5
Name Bilirubin test
Definition Bilirubin testing checks for levels of bilirubin in your blood.
Why is done
Bilirubin testing is usually done as part of a group of tests to check the health of your liver. Bilirubin
testing may be done to: Investigate jaundice — elevated levels of bilirubin can cause yellowing of
your skin and the whites of your eyes (jaundice). A common use of the test is to measure bilirubin
levels in newborns, determine whether there might be blockage in your liver's bile ducts, help detect or
monitor the progression of other liver disease, such as hepatitis, help detect increased destruction of red
blood cells, help follow how a treatment is working, help evaluate suspected drug toxicity.
Preparation None
Expectation
Bilirubin testing is done using a blood sample. Usually, the blood is drawn through a small needle
inserted into a vein in the bend of your arm. The needle is attached to a small tube, in which your blood
is collected.You may feel a quick pain as the needle is inserted into your arm and experience some
short-term discomfort at the site after the needle is removed.
Risks None
Results
Normal results for a bilirubin test are 1.2 milligrams per deciliter (mg/dL) of total bilirubin for adults,
and usually 1 mg/dL for those under 18. Normal results for direct bilirubin are generally 0.3 mg/dL.')
Table 4. Tests table in database
Recommended treatments for the most related symptoms are demonstrated as in Table 5. Treatments are
classified with as their ID numbers, names and definitions.
ID 1
Name Open abdominal surgery'
Definition
If you have an abdominal aortic aneurysm, surgery is generally recommended if your aneurysm is about
1.9 to 2.2 inches (about 5 to 5.5 centimeters) or larger. Open abdominal surgery to repair an abdominal
aortic aneurysm involves removing the damaged section of the aorta and replacing it with a synthetic
tube (graft), which is sewn into place. This procedure requires open abdominal surgery, and it will
generally take you a month or more to fully recover.
Table 6. Table of treatments in database
5. E-Symptom Analysis System to Improve…
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Implementations: An Intelligent context utilizing recommendation engine (I CURE) for medical diagnosis is
developed to convert the clinical data into significant and effective information. Python is used to develop the
most efficient and appropriate model. Text Blob is a library used for input and output processing, and for string
matching which actually classifies input symptoms as a disease. Two sets are used for classification, one including
only symptoms, and the other the matching diseases. Details about diseases such as treatments and tests are
recommended, are stored in MySQL database. Firstly, the user is asked to enter his/her symptoms, and then the
application converts the answer into Text Blob object. Fuzzy String Matching, also called approximate string
matching, is implemented as the process of finding strings which approximately match a given pattern. The
closeness of a match is often measured in terms of edit distance which is the number of primitive operations
necessary to convert the string into an exact match.
Training: In training process text-based symptoms, patient`s personal information and past medical history is
used as input data. In the next step, data is trained for the possible detected diagnoses and recommend appropriate
treatment and as a result of training we expect to get out model output.
Figure 3. Implementation steps for training process
Testing: After the training process, the system is tested for various diagnoses and patients, then the percentage
risk of possible disease is represented as output information. Corresponding to this, treatments and
recommendations (any medical examinations, tests) are driven.
Figure 4. Procedure of testing and inferences
IV. RESULTS AND CONCLUSION
Symptom analysis system, I-CURE (Intelligent context utilizing recommendation engine) is developed to increase
the accuracy of medical diagnosis. The project may provide a significant help in clinical decision process which
gives effective results even with patients own words as symptoms. The behavior of different classifiers was tested
in the context of the problem. classifying inputted symptoms into predefined disease classes. The problem was
approached with three different methods: using naïve Bayes, decision tree and Fuzzy Wuzzy library.
The goal was to make a system that will give as correct classification as possible regardless of spelling mistakes.
Different inputs were tested to assess the abilities supported by the Text Blob library. Output is based on the result
obtained using Fuzzy Wuzzy library regardless of some spelling mistakes that user might have done in giving
input. After testing the system, an accuracy of 72.5% has been accomplished. The impact on outcomes, assessing
whether the project reduces time from diagnosis to treatment, reduces cost, and improves quality the benefits of
the study in global health care environment.
Future Study Objectives: Detailed information about the patient will also be collected to evaluate the model
efficiently and give more accurate prediction of treatments and recommendations. These are patients past medical
6. E-Symptom Analysis System to Improve…
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history (allergies, medicines, surgeries, family history, diets, and habits), birth and growth information, age,
gender, height, weight. To improve the current system, we aim to upgrade I-CURE available without restriction
of input language.
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