Fatemeh Rangraz Jeddi, F. Atoof, R. Farrahi, Sara Chopannejad
Introduction: Medical tourism is the most important aspect of health tourism. The responsibilities of this industry are mostly undertaken by agencies and facilitators acting as intermediaries between patients and service providers. As a key factor, websites provide extensive services to patients for a better presence in medical tourism market. The present study aimed to compare medical tourism websites and facilitators in Iran and other countries using correspondence analysis.Method: Websites were selected based on the specified criteria such as content of websites which were examined using content analysis technique. The data belonging to website content were classified into two groups including medical and tourism services and information and communication issues. Correspondence analysis was done using two R packages (FactoMineR for analysis and fact extra for data visualization).Results: Of 42 selected websites, 19 was belonged to Iran, 11 to North America, 7 to South and Central America, and 5 to Asia. Medical tourism facilitators in North America and Asia tend to provide modern contact and legal information. Against Iranians' facilitators tend to show traditional contact and general information. South American websites provide more information about hospital accreditation. Iranian websites emphasized tourism-related information. Whereas, North American’s are emphasized on cost-comparison lists.Conclusion: Results of the present study provide a snapshot of status of data provided on websites in terms of medical, tourist and communication services available in the studied websites and clearly showed that Iranian medical tourism facilitator websites act differently from those of other countries. Websites play important roles for guiding customers to make decisions regarding the medical journey. Therefore, Iranian medical tourism facilitator websites must reduce their differences with those of other countries in order to be more actively participate and earn more profit in this competitive market.
{"title":"Comparing the Content of Medical Tourism Facilitator Websites in Iran And Other Countries: A Correspondence Analysis","authors":"Fatemeh Rangraz Jeddi, F. Atoof, R. Farrahi, Sara Chopannejad","doi":"10.30699/fhi.v8i1.188","DOIUrl":"https://doi.org/10.30699/fhi.v8i1.188","url":null,"abstract":"Introduction: Medical tourism is the most important aspect of health tourism. The responsibilities of this industry are mostly undertaken by agencies and facilitators acting as intermediaries between patients and service providers. As a key factor, websites provide extensive services to patients for a better presence in medical tourism market. The present study aimed to compare medical tourism websites and facilitators in Iran and other countries using correspondence analysis.Method: Websites were selected based on the specified criteria such as content of websites which were examined using content analysis technique. The data belonging to website content were classified into two groups including medical and tourism services and information and communication issues. Correspondence analysis was done using two R packages (FactoMineR for analysis and fact extra for data visualization).Results: Of 42 selected websites, 19 was belonged to Iran, 11 to North America, 7 to South and Central America, and 5 to Asia. Medical tourism facilitators in North America and Asia tend to provide modern contact and legal information. Against Iranians' facilitators tend to show traditional contact and general information. South American websites provide more information about hospital accreditation. Iranian websites emphasized tourism-related information. Whereas, North American’s are emphasized on cost-comparison lists.Conclusion: Results of the present study provide a snapshot of status of data provided on websites in terms of medical, tourist and communication services available in the studied websites and clearly showed that Iranian medical tourism facilitator websites act differently from those of other countries. Websites play important roles for guiding customers to make decisions regarding the medical journey. Therefore, Iranian medical tourism facilitator websites must reduce their differences with those of other countries in order to be more actively participate and earn more profit in this competitive market. ","PeriodicalId":154611,"journal":{"name":"Frontiers in Health Informatics","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129143661","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Z. Karbasi, K. Bahaadinbeigy, L. Ahmadian, Reza Khajouei, M. Mirzaee
Introduction: Speech recognition(SR) technology has been existing for more than two decades. But, it has been rarely used in health care institutions and not applied uniformly in all the clinical domains. The aim of this study was to investigate the accuracy of speech recognition system in four different situations in the real environment of health services. We also report physicians' experience of using speech recognition technology.Method:. To do this study, NEVISA SR software professional v.3 was installed on the computers of expert physicians. The pre-designated medical report was tested by the physicians in four different modes including slow expression in a silent environment, slow expression in crowded environments, rapid expression in a silent environment and rapid expression in a busy environment. After using the speech recognition software by 15 physicians in hospitals, a designed questionnaire was distributed among them. .Results: The results showed that the highest average accuracy of speech recognition software was in the silent environment by slow expression and the minimum average accuracy was in the busy environment by rapid expression. Of all the participants in the study, 53.3% of the physicians believed that the use of speech recognition system promoted the workflow.Conclusion: We found that software accuracy was generally higher than the expectation and its use required to upgrade the system and its operation. In order to achieve the highest level of recognition rate and error reduction by speech recognition, influential factors such as environmental noise, type of software or hardware, training and experience of participants can be also considered.
{"title":"Accuracy of Speech Recognition System’s Medical Report and Physicians' Experience in Hospitals","authors":"Z. Karbasi, K. Bahaadinbeigy, L. Ahmadian, Reza Khajouei, M. Mirzaee","doi":"10.30699/FHI.V8I1.199","DOIUrl":"https://doi.org/10.30699/FHI.V8I1.199","url":null,"abstract":"Introduction: Speech recognition(SR) technology has been existing for more than two decades. But, it has been rarely used in health care institutions and not applied uniformly in all the clinical domains. The aim of this study was to investigate the accuracy of speech recognition system in four different situations in the real environment of health services. We also report physicians' experience of using speech recognition technology.Method:. To do this study, NEVISA SR software professional v.3 was installed on the computers of expert physicians. The pre-designated medical report was tested by the physicians in four different modes including slow expression in a silent environment, slow expression in crowded environments, rapid expression in a silent environment and rapid expression in a busy environment. After using the speech recognition software by 15 physicians in hospitals, a designed questionnaire was distributed among them. .Results: The results showed that the highest average accuracy of speech recognition software was in the silent environment by slow expression and the minimum average accuracy was in the busy environment by rapid expression. Of all the participants in the study, 53.3% of the physicians believed that the use of speech recognition system promoted the workflow.Conclusion: We found that software accuracy was generally higher than the expectation and its use required to upgrade the system and its operation. In order to achieve the highest level of recognition rate and error reduction by speech recognition, influential factors such as environmental noise, type of software or hardware, training and experience of participants can be also considered.","PeriodicalId":154611,"journal":{"name":"Frontiers in Health Informatics","volume":"101 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125674436","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
F. Moghbeli, Tina Adel, M. Langarizadeh, Mitra Hakim Shoushtari
Introduction: The personal health record of patient with autism has not been adequately addressed. While, these records play an important role to provide a good perspective on how to diagnose autism, negotiating, coordinating and designing services and interventions by families and physicians during delivery of multiple services. The present study is aimed to present a conceptual model of electronic personal health record for patients with autism.Material and Methods: This study was conducted on six psychiatric practitioners and six pediatricians from Raoul-e-Akram Hospital and Ali Asghar Hospital with purposeful sampling. A questionnaire has been used for data gathering and identifying information needs. The content validity was measured using expert panel method and test-retest method (r=0.79) was used to perform the reliability test.Results: According to the findings, the most important data elements of the conceptual model of the personal health record for patients with autism from the viewpoint of physicians are divided into two demographic data segments including first name, father's name, national code, Age, gender, marital status, address and telephone, and clinical data including maternal gestational age, family history, parental relationship, history of developmental delay, name of patient's drug use, test results, age of the first diagnosis of autism , seizure, mental retardation, early diagnosis, treatment history and individual function level (based on valid clinical scales) such as a general clinical measure .Conclusion: Since autism patients’ long life clinical information that recorded in their electronic health records system plays an important role in diagnosis and management of patients' clinical problems, the conceptual model of personal health record for patients with autism could have a significant effect in managing and integrating patient clinical information, increasing the quality of care, and reducing the cost of treatment and diagnosis.
{"title":"A Conceptual Model of Personal Health Record for Autistic Patients","authors":"F. Moghbeli, Tina Adel, M. Langarizadeh, Mitra Hakim Shoushtari","doi":"10.30699/fhi.v8i1.197","DOIUrl":"https://doi.org/10.30699/fhi.v8i1.197","url":null,"abstract":"Introduction: The personal health record of patient with autism has not been adequately addressed. While, these records play an important role to provide a good perspective on how to diagnose autism, negotiating, coordinating and designing services and interventions by families and physicians during delivery of multiple services. The present study is aimed to present a conceptual model of electronic personal health record for patients with autism.Material and Methods: This study was conducted on six psychiatric practitioners and six pediatricians from Raoul-e-Akram Hospital and Ali Asghar Hospital with purposeful sampling. A questionnaire has been used for data gathering and identifying information needs. The content validity was measured using expert panel method and test-retest method (r=0.79) was used to perform the reliability test.Results: According to the findings, the most important data elements of the conceptual model of the personal health record for patients with autism from the viewpoint of physicians are divided into two demographic data segments including first name, father's name, national code, Age, gender, marital status, address and telephone, and clinical data including maternal gestational age, family history, parental relationship, history of developmental delay, name of patient's drug use, test results, age of the first diagnosis of autism , seizure, mental retardation, early diagnosis, treatment history and individual function level (based on valid clinical scales) such as a general clinical measure .Conclusion: Since autism patients’ long life clinical information that recorded in their electronic health records system plays an important role in diagnosis and management of patients' clinical problems, the conceptual model of personal health record for patients with autism could have a significant effect in managing and integrating patient clinical information, increasing the quality of care, and reducing the cost of treatment and diagnosis.","PeriodicalId":154611,"journal":{"name":"Frontiers in Health Informatics","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123652810","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A. Kazemi, H. Salmani, A. Shakibafard, Farhad Fatehi
Introduction: The popularity of mobile phone applications (Apps) and wearable devices for medical and health purposes is on the rise, but not all the mobile health (mHealth) innovative solutions that hit the news every day will sustain and have an impact on the health of people. The aim of this news-based horizon scanning study was to explore and identify new and emerging mobile technologies that are likely to impact the future of health and medical care.Methods: We conducted a systematic search on top ranking technology websites, according to Alexa Ranking, to identify health-related mobile-based technologies. We followed the EuroScan guide for horizon scanning, which recommends four steps: identification, filtering, prioritization, evaluation and conclusion. Technologies of interest were mHealth technologies regardless of their maturity level. The impact of technologies was assessed and scored in four areas: user, technology, safety, and cost.Results: Five hundred news articles were identified through the electronic search. After screening, 106 mHealth innovative technologies were included in this study. We categorized the included technologies into three groups: mobile apps (n=37), smart-connected devices (n=19), and wearables (n=50). mHealth technologies were most frequently developed for preventive health services, mental health services and rehabilitation services. There was no remarkable difference between the technology groups in terms of safety and adverse effects, but the groups were significantly different in terms of the target population, technology, and cost.Conclusion: An increasing number of solutions based on mobile technology is being developed by both public and private sectors but a low proportion of them undergo proper scientific evaluations. Despite the commercial availability of many innovative mobile apps, wearables, and smart connected devices, few of them have been actually used in clinics, hospitals, and health centers. There is a clear need for changes in healthcare service models to unlock the full potential of these innovative technologies.
{"title":"New and Emerging Mobile Technologies for Healthcare (mHealth): A Horizon Scanning Study","authors":"A. Kazemi, H. Salmani, A. Shakibafard, Farhad Fatehi","doi":"10.30699/FHI.V8I1.196","DOIUrl":"https://doi.org/10.30699/FHI.V8I1.196","url":null,"abstract":"Introduction: The popularity of mobile phone applications (Apps) and wearable devices for medical and health purposes is on the rise, but not all the mobile health (mHealth) innovative solutions that hit the news every day will sustain and have an impact on the health of people. The aim of this news-based horizon scanning study was to explore and identify new and emerging mobile technologies that are likely to impact the future of health and medical care.Methods: We conducted a systematic search on top ranking technology websites, according to Alexa Ranking, to identify health-related mobile-based technologies. We followed the EuroScan guide for horizon scanning, which recommends four steps: identification, filtering, prioritization, evaluation and conclusion. Technologies of interest were mHealth technologies regardless of their maturity level. The impact of technologies was assessed and scored in four areas: user, technology, safety, and cost.Results: Five hundred news articles were identified through the electronic search. After screening, 106 mHealth innovative technologies were included in this study. We categorized the included technologies into three groups: mobile apps (n=37), smart-connected devices (n=19), and wearables (n=50). mHealth technologies were most frequently developed for preventive health services, mental health services and rehabilitation services. There was no remarkable difference between the technology groups in terms of safety and adverse effects, but the groups were significantly different in terms of the target population, technology, and cost.Conclusion: An increasing number of solutions based on mobile technology is being developed by both public and private sectors but a low proportion of them undergo proper scientific evaluations. Despite the commercial availability of many innovative mobile apps, wearables, and smart connected devices, few of them have been actually used in clinics, hospitals, and health centers. There is a clear need for changes in healthcare service models to unlock the full potential of these innovative technologies.","PeriodicalId":154611,"journal":{"name":"Frontiers in Health Informatics","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127500031","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Introduction: The use of healthcare frameworks and, in particular, policy makers is crucial for designing and evaluating systems. Frameworks provide the ability to measure and compare health system functions in different countries in order to make better and more meaningful decisions, to make comparisons within and between countries, identifying gaps, and sharing information. Researchers also have the ability to use the dimensions of the frameworks to measure progress over time. Due to the importance of the subject, the purpose of this study is to describe the framework concepts and the introduction of framework applications in the field of health care.Material and Methods: This study is based on a search of the ProQuest, PubMed, Google Scholar, Science Direct, Scopus, IranMedex, Irandoc, Magiran, ParsMedline and Scientific Information Database (SID) databases, as well as the study of specialized keyword web sites and the standard was done. After a thorough study, 50 sources were selected according to the study objectives and were used to formulate the final article.Results: The framework can be used to manage health system investments, identify important research areas in the field of health, and define new and useful research.Conclusion: Given the importance of the health framework, the need to provide a framework for other critical health care sectors is essential.
引言:卫生保健框架的使用，特别是政策制定者的使用，对于系统的设计和评估至关重要。框架提供了衡量和比较不同国家卫生系统功能的能力，以便做出更好和更有意义的决定，在国家内部和国家之间进行比较，确定差距并共享信息。研究人员也有能力使用框架的维度来衡量一段时间内的进展。由于本课题的重要性，本研究的目的是描述框架的概念，并介绍框架在卫生保健领域的应用。材料与方法:本研究基于对ProQuest、PubMed、Google Scholar、Science Direct、Scopus、IranMedex、Irandoc、Magiran、ParsMedline和Scientific Information Database (SID)数据库的检索，以及对专业关键词网站和标准的研究。经过深入的研究，根据研究目标选择了50个来源，并用于制定最终的文章。结果:该框架可用于管理卫生系统投资，确定卫生领域的重要研究领域，并确定新的和有用的研究。结论:鉴于卫生框架的重要性，必须为其他关键的卫生保健部门提供一个框架。
{"title":"Applications of Framework In Health Care: A Survey","authors":"Elham Nazari, M. Shahriari, H. Tabesh","doi":"10.30699/FHI.V8I1.186","DOIUrl":"https://doi.org/10.30699/FHI.V8I1.186","url":null,"abstract":"Introduction: The use of healthcare frameworks and, in particular, policy makers is crucial for designing and evaluating systems. Frameworks provide the ability to measure and compare health system functions in different countries in order to make better and more meaningful decisions, to make comparisons within and between countries, identifying gaps, and sharing information. Researchers also have the ability to use the dimensions of the frameworks to measure progress over time. Due to the importance of the subject, the purpose of this study is to describe the framework concepts and the introduction of framework applications in the field of health care.Material and Methods: This study is based on a search of the ProQuest, PubMed, Google Scholar, Science Direct, Scopus, IranMedex, Irandoc, Magiran, ParsMedline and Scientific Information Database (SID) databases, as well as the study of specialized keyword web sites and the standard was done. After a thorough study, 50 sources were selected according to the study objectives and were used to formulate the final article.Results: The framework can be used to manage health system investments, identify important research areas in the field of health, and define new and useful research.Conclusion: Given the importance of the health framework, the need to provide a framework for other critical health care sectors is essential.","PeriodicalId":154611,"journal":{"name":"Frontiers in Health Informatics","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116018736","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Introduction: Thresholding is one of the most important parts of segmentation whenever we want to detect a specific part of image. There are several thresholding methods that previous researchers used them frequently as bi-level techniques such as DBT or multilevel such as 3S. New histogram feature thresholding method is implemented to detect lesion area in digital mammograms and compared with 3S (Shrinking-Search-Space) multithresholding and FCM method in terms of segmentation quality and segmentation time as a benchmark in thresholding.Materials and Methods: These algorithms have been tested on 188 digital mammograms. Digital mammogram image used after preprocessing which was including crop the unnecessary area, resize the image into 1024 by 1024 pixel and then normalize pixel values by using simple contrast stretching method.Results: The results show that suggested method results are not similar with 3S and FCM methods, and it is faster than other methods. This is another superiority of suggested method with respect to others. Results of previous studies showed that FCM is not a reliable clustering algorithm and it needs several run to give us a reliable result (1). Results of this study also showed that this approach is correct.Conclusions: The suggested method may used as a reliable thresholding method in order to detection of lesion area.
{"title":"Comparison of Histogram Feature Based Thresholding with 3S Multi-Thresholding and Fuzzy C-Means","authors":"M. Langarizadeh, R. Mahmud","doi":"10.30699/FHI.V8I1.195","DOIUrl":"https://doi.org/10.30699/FHI.V8I1.195","url":null,"abstract":"Introduction: Thresholding is one of the most important parts of segmentation whenever we want to detect a specific part of image. There are several thresholding methods that previous researchers used them frequently as bi-level techniques such as DBT or multilevel such as 3S. New histogram feature thresholding method is implemented to detect lesion area in digital mammograms and compared with 3S (Shrinking-Search-Space) multithresholding and FCM method in terms of segmentation quality and segmentation time as a benchmark in thresholding.Materials and Methods: These algorithms have been tested on 188 digital mammograms. Digital mammogram image used after preprocessing which was including crop the unnecessary area, resize the image into 1024 by 1024 pixel and then normalize pixel values by using simple contrast stretching method.Results: The results show that suggested method results are not similar with 3S and FCM methods, and it is faster than other methods. This is another superiority of suggested method with respect to others. Results of previous studies showed that FCM is not a reliable clustering algorithm and it needs several run to give us a reliable result (1). Results of this study also showed that this approach is correct.Conclusions: The suggested method may used as a reliable thresholding method in order to detection of lesion area.","PeriodicalId":154611,"journal":{"name":"Frontiers in Health Informatics","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116655407","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Introduction: Health care data is increasing. The correct analysis of such data will improve the quality of care and reduce costs. This kind of data has certain features such as high volume, variety, high-speed production, etc. It makes it impossible to analyze with ordinary hardware and software platforms. Choosing the right platform for managing this kind of data is very important. The purpose of this study is to introduce and compare the most popular and most widely used platform for processing big data, Apache Hadoop MapReduce, and the two Apache Spark and Apache Flink platforms, which have recently been featured with great prominence.Material and Methods: This study is a survey whose content is based on the subject matter search of the Proquest, PubMed, Google Scholar, Science Direct, Scopus, IranMedex, Irandoc, Magiran, ParsMedline and Scientific Information Database (SID) databases, as well as Web reviews, specialized books with related keywords and standard. Finally, 80 articles related to the subject of the study were reviewed.Results: The findings showed that each of the studied platforms has features, such as data processing, support for different languages, processing speed, computational model, memory management, optimization, delay, error tolerance, scalability, performance, compatibility, Security and so on. Overall, the findings showed that the Apache Hadoop environment has simplicity, error detection, and scalability management based on clusters, but because its processing is based on batch processing, it works for slow complex analyzes and does not support flow processing, Apache Spark is also distributed as a computational platform that can process a big data set in memory with a very fast response time, the Apache Flink allows users to store data in memory and load them multiple times and provide a complex Fault Tolerance mechanism Continuously retrieves data flow status.Conclusion: The application of big data analysis and processing platforms varies according to the needs. In other words, it can be said that each technology is complementary, each of which is applicable in a particular field and cannot be separated from one another and depending on the purpose and the expected expectation, and the platform must be selected for analysis or whether custom tools are designed on these platforms.
{"title":"BigData Analysis in Healthcare: Apache Hadoop , Apache spark and Apache Flink","authors":"Elham Nazari, M. Shahriari, H. Tabesh","doi":"10.30699/FHI.V8I1.180","DOIUrl":"https://doi.org/10.30699/FHI.V8I1.180","url":null,"abstract":"Introduction: Health care data is increasing. The correct analysis of such data will improve the quality of care and reduce costs. This kind of data has certain features such as high volume, variety, high-speed production, etc. It makes it impossible to analyze with ordinary hardware and software platforms. Choosing the right platform for managing this kind of data is very important. The purpose of this study is to introduce and compare the most popular and most widely used platform for processing big data, Apache Hadoop MapReduce, and the two Apache Spark and Apache Flink platforms, which have recently been featured with great prominence.Material and Methods: This study is a survey whose content is based on the subject matter search of the Proquest, PubMed, Google Scholar, Science Direct, Scopus, IranMedex, Irandoc, Magiran, ParsMedline and Scientific Information Database (SID) databases, as well as Web reviews, specialized books with related keywords and standard. Finally, 80 articles related to the subject of the study were reviewed.Results: The findings showed that each of the studied platforms has features, such as data processing, support for different languages, processing speed, computational model, memory management, optimization, delay, error tolerance, scalability, performance, compatibility, Security and so on. Overall, the findings showed that the Apache Hadoop environment has simplicity, error detection, and scalability management based on clusters, but because its processing is based on batch processing, it works for slow complex analyzes and does not support flow processing, Apache Spark is also distributed as a computational platform that can process a big data set in memory with a very fast response time, the Apache Flink allows users to store data in memory and load them multiple times and provide a complex Fault Tolerance mechanism Continuously retrieves data flow status.Conclusion: The application of big data analysis and processing platforms varies according to the needs. In other words, it can be said that each technology is complementary, each of which is applicable in a particular field and cannot be separated from one another and depending on the purpose and the expected expectation, and the platform must be selected for analysis or whether custom tools are designed on these platforms.","PeriodicalId":154611,"journal":{"name":"Frontiers in Health Informatics","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133069644","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Leila R. Kalankesh, Ehsan Mohammadian, Mahdi Ghalandari, Abbas Delpasand, Hossain Aghayari
Introduction: Understanding the information seeking behavior of individuals, especially students who are more likely to seek health information than other people, can be seen as an opportunity to provide resources to improve lifestyle or prevent possible health threatening behaviors among students. The main objective of this research is to determine the HISB among students of Tabriz University of Medical Sciences (TUOMS).Material and Methods: This descriptive cross-sectional study was carried out at TUOMS among students in 2017 through using simple random sampling method.Results: The results showed that most of the students had experience of searching information about prevention of illness (47.8%) and general health knowledge (45.1%). The common outcomes of accessing health information by students were their decision to visit the physician (68.2%) and relieving their concern about their condition or illness (60.2%).Conclusion: The results of this study indicate that most students are searching for information on diet, physical activity and physical health.
{"title":"Health Information Seeking Behavior (HISB) among the University Students","authors":"Leila R. Kalankesh, Ehsan Mohammadian, Mahdi Ghalandari, Abbas Delpasand, Hossain Aghayari","doi":"10.30699/FHI.V8I1.189","DOIUrl":"https://doi.org/10.30699/FHI.V8I1.189","url":null,"abstract":"Introduction: Understanding the information seeking behavior of individuals, especially students who are more likely to seek health information than other people, can be seen as an opportunity to provide resources to improve lifestyle or prevent possible health threatening behaviors among students. The main objective of this research is to determine the HISB among students of Tabriz University of Medical Sciences (TUOMS).Material and Methods: This descriptive cross-sectional study was carried out at TUOMS among students in 2017 through using simple random sampling method.Results: The results showed that most of the students had experience of searching information about prevention of illness (47.8%) and general health knowledge (45.1%). The common outcomes of accessing health information by students were their decision to visit the physician (68.2%) and relieving their concern about their condition or illness (60.2%).Conclusion: The results of this study indicate that most students are searching for information on diet, physical activity and physical health.","PeriodicalId":154611,"journal":{"name":"Frontiers in Health Informatics","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131119389","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Introduction: In the field of health, information and communication technology plays an important role, the world is experiencing the era of communication, the field of health is not asymmetrical. According to the study, Iran is one of the countries that is at high risk of diabetes, and continues to increase in Iran and in most countries. The purpose of this paper is to review the literature on the effectiveness of Information and Communication Technology (ICTs) in the treatment of type 1 and type 2 diabetes.Material and Methods: This study was conducted as a review and through a search of valid information databases such as PubMed, Science direct, and Google Scholar. After the final extraction from the 106 papers in the cellular field 37% and 36% in telemedicine and 27% in the Internet topic from 2010 to 2018, were finalized.Results: The findings of the study showed that the recent developments in information technology combined with services for cost optimization have increased and the current use of information technology (IT) offers unique opportunities for patients with diabetes. Internet, mobile phone and telemedicine services can facilitate and improve communication between patients and healthcare professionals and play an important role in managing diabetes. The growing challenge is the proper management of diabetes to play an important role by employing innovative approaches aimed at improving patient outcomes and reducing the incidence of adverse healthcare systems.Conclusion: This study is an overview of information and communication technology research in diabetes management and can help researchers measure the effectiveness of information and communication technology in diabetes self-care and therapeutic systems in different areas and motivate self-management. Cost reduction, technology acceptance and satisfaction.
{"title":"Review of the Effectiveness of Information and Communication Technology (ICTs) in the Treatment of Type 1 and Type 2 Diabetes","authors":"Parnian Asgari, Elham Nazari","doi":"10.30699/FHI.V8I1.182","DOIUrl":"https://doi.org/10.30699/FHI.V8I1.182","url":null,"abstract":"Introduction: In the field of health, information and communication technology plays an important role, the world is experiencing the era of communication, the field of health is not asymmetrical. According to the study, Iran is one of the countries that is at high risk of diabetes, and continues to increase in Iran and in most countries. The purpose of this paper is to review the literature on the effectiveness of Information and Communication Technology (ICTs) in the treatment of type 1 and type 2 diabetes.Material and Methods: This study was conducted as a review and through a search of valid information databases such as PubMed, Science direct, and Google Scholar. After the final extraction from the 106 papers in the cellular field 37% and 36% in telemedicine and 27% in the Internet topic from 2010 to 2018, were finalized.Results: The findings of the study showed that the recent developments in information technology combined with services for cost optimization have increased and the current use of information technology (IT) offers unique opportunities for patients with diabetes. Internet, mobile phone and telemedicine services can facilitate and improve communication between patients and healthcare professionals and play an important role in managing diabetes. The growing challenge is the proper management of diabetes to play an important role by employing innovative approaches aimed at improving patient outcomes and reducing the incidence of adverse healthcare systems.Conclusion: This study is an overview of information and communication technology research in diabetes management and can help researchers measure the effectiveness of information and communication technology in diabetes self-care and therapeutic systems in different areas and motivate self-management. Cost reduction, technology acceptance and satisfaction.","PeriodicalId":154611,"journal":{"name":"Frontiers in Health Informatics","volume":"391 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121575423","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
F. Sepehri, M. Langarizadeh, L. Sharifi, G. Azizi, R. Safdari, A. Aghamohammadi
Introduction: Primary immunodeficiency diseases (PID) are generally rare genetic disorders affecting the immune system. Overlapping PIDs symptoms and signs is a challenge to diagnosis and treatment. On the other hand, remembering of all diagnosis criteria is difficult for practitioners. The purpose of this research is developing guideline-based clinical decision support system for diagnosis of primary immune deficiency diseases, to assist practitioner in order to diagnose of disease in early stage and to minimize complications of such diseases.Material and Methods: To provide data a checklist was used and most important demographic information, symptoms, family history, physical findings and laboratory findings to diagnose eight common PIDs extracted from guidelines and literature under specialists opinion. The diagnosis inference model design and develop in Protégé (version 3.4.8) frame based ontology modeling using "Noy and McGuinness" method. Then the mobile based inference model in Eclipse (SDK version 3.7.1) software has been developed and clinical decision support system of primary immunodeficiency has been created.Results: To design the diagnosis inference model in Protégé software, data were classified in 5 main classes and 24 subclasses as hierarchical. Then, specific properties of each class, and determine the value of each property. Then define Instances of each class and initialized instance properties. Then use this model to develop CDSS based on mobile in Eclipse software. At the end, the inference model and the CDSS test with 110 patient’s record data and both of them recognized all 110 patient correctly such as specialist recognition.Conclusion:Guideline-based decision support systems help to detect diseases correctly, quickly and early. Guideline-based decision support systems are very reliable to practitioner, because guidelines are accepted to their. These systems reduce the forget probability of diagnosis stages and percentage error of diagnosis by practitioner and increase the accuracy of diagnosis.
原发性免疫缺陷疾病(PID)是一种罕见的影响免疫系统的遗传性疾病。症状和体征重叠是诊断和治疗的挑战。另一方面，医生很难记住所有的诊断标准。本研究的目的是开发基于指南的原发性免疫缺乏性疾病诊断的临床决策支持系统，以帮助医生在疾病的早期诊断和减少此类疾病的并发症。材料和方法:根据专家意见，从指南和文献中提取8种常见的pid，使用检查表和最重要的人口统计学信息、症状、家族史、体格检查和实验室检查结果来诊断。采用“Noy and McGuinness”方法，设计开发了基于prot(3.4.8版)框架的本体建模中的诊断推理模型。然后在Eclipse (SDK版本3.7.1)软件中开发基于移动端的推理模型，创建原发性免疫缺陷临床决策支持系统。结果:在prot软件中设计诊断推理模型，将数据分为5个主要类和24个亚类进行分层。然后，确定每个类的具体属性，并确定每个属性的值。然后定义每个类的实例并初始化实例属性。然后利用该模型在Eclipse软件中开发了基于移动端的CDSS。最后，对110例患者的病历数据进行推理模型和CDSS测试，两者均正确识别了全部110例患者，如专家识别。结论:基于指南的决策支持系统有助于正确、快速、早期发现疾病。基于指南的决策支持系统对于从业者来说是非常可靠的，因为指南被他们所接受。这些系统降低了医生对诊断阶段的遗忘概率和诊断错误率，提高了诊断的准确性。
{"title":"Development A Guideline-based Decision Support System to Diagnosis of Primary Immunodeficiency Diseases","authors":"F. Sepehri, M. Langarizadeh, L. Sharifi, G. Azizi, R. Safdari, A. Aghamohammadi","doi":"10.30699/IJMI.V8I1.184","DOIUrl":"https://doi.org/10.30699/IJMI.V8I1.184","url":null,"abstract":"Introduction: Primary immunodeficiency diseases (PID) are generally rare genetic disorders affecting the immune system. Overlapping PIDs symptoms and signs is a challenge to diagnosis and treatment. On the other hand, remembering of all diagnosis criteria is difficult for practitioners. The purpose of this research is developing guideline-based clinical decision support system for diagnosis of primary immune deficiency diseases, to assist practitioner in order to diagnose of disease in early stage and to minimize complications of such diseases.Material and Methods: To provide data a checklist was used and most important demographic information, symptoms, family history, physical findings and laboratory findings to diagnose eight common PIDs extracted from guidelines and literature under specialists opinion. The diagnosis inference model design and develop in Protégé (version 3.4.8) frame based ontology modeling using \"Noy and McGuinness\" method. Then the mobile based inference model in Eclipse (SDK version 3.7.1) software has been developed and clinical decision support system of primary immunodeficiency has been created.Results: To design the diagnosis inference model in Protégé software, data were classified in 5 main classes and 24 subclasses as hierarchical. Then, specific properties of each class, and determine the value of each property. Then define Instances of each class and initialized instance properties. Then use this model to develop CDSS based on mobile in Eclipse software. At the end, the inference model and the CDSS test with 110 patient’s record data and both of them recognized all 110 patient correctly such as specialist recognition.Conclusion:Guideline-based decision support systems help to detect diseases correctly, quickly and early. Guideline-based decision support systems are very reliable to practitioner, because guidelines are accepted to their. These systems reduce the forget probability of diagnosis stages and percentage error of diagnosis by practitioner and increase the accuracy of diagnosis.","PeriodicalId":154611,"journal":{"name":"Frontiers in Health Informatics","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126519749","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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