Introduction: Various training methods such as web-based training tools have been developed to achieve the potential benefits of classification systems developed by the World Health Organization (WHO). Given that users of these tools have different levels of capability, usability problems could reduce the speed and accuracy of learning among users interacting with these tools. This study aims to identify usability problems of web-based training tools under the WHO family of international classifications (WHO-FIC).Methods: In this descriptive and cross-sectional study, ten trained evaluators independently examined WHO-FIC training tools using the heuristic evaluation method. The identified problems were classified into 10 Nielsen’s usability heuristics. Then, their average severity was calculated.Results: In total, 40 usability problems were identified after merging and eliminating the duplicates. The highest number of problems was related to ICD-10 training tool (n=20). The highest number of problems was related to heuristics of aesthetic and minimalist design (25.0%), and user control and freedom (17.5%). Heuristics of flexibility and efficiency of use and helping users recognize, diagnose and recover from errors had the highest average severity of problems.Conclusion: Violating heuristics of aesthetic and minimalist design, user control and freedom and recognition rather than recall were among the most common problems of WHO-FIC training tools. Evaluators reported that half of the user interface problems of WHO-FIC training tools were of major and catastrophe type. Solving the usability problems of these tools could lead to ease of work, increased speed of learning and acceptance of these systems among users.
{"title":"Usability Evaluation of Web-based Training Tools under WHO Family of International Classifications (WHO-FIC)","authors":"Farzad Salmanizadeh, L. Ahmadian, A. Ameri","doi":"10.30699/fhi.v12i0.409","DOIUrl":"https://doi.org/10.30699/fhi.v12i0.409","url":null,"abstract":"Introduction: Various training methods such as web-based training tools have been developed to achieve the potential benefits of classification systems developed by the World Health Organization (WHO). Given that users of these tools have different levels of capability, usability problems could reduce the speed and accuracy of learning among users interacting with these tools. This study aims to identify usability problems of web-based training tools under the WHO family of international classifications (WHO-FIC).Methods: In this descriptive and cross-sectional study, ten trained evaluators independently examined WHO-FIC training tools using the heuristic evaluation method. The identified problems were classified into 10 Nielsen’s usability heuristics. Then, their average severity was calculated.Results: In total, 40 usability problems were identified after merging and eliminating the duplicates. The highest number of problems was related to ICD-10 training tool (n=20). The highest number of problems was related to heuristics of aesthetic and minimalist design (25.0%), and user control and freedom (17.5%). Heuristics of flexibility and efficiency of use and helping users recognize, diagnose and recover from errors had the highest average severity of problems.Conclusion: Violating heuristics of aesthetic and minimalist design, user control and freedom and recognition rather than recall were among the most common problems of WHO-FIC training tools. Evaluators reported that half of the user interface problems of WHO-FIC training tools were of major and catastrophe type. Solving the usability problems of these tools could lead to ease of work, increased speed of learning and acceptance of these systems among users.","PeriodicalId":154611,"journal":{"name":"Frontiers in Health Informatics","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122066808","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: Breast cancer is one of the most common cancers among women compared to all other ones. Machine learning techniques can bring a large contribute on the process of prediction and early diagnosis of breast cancer, became a research hotspot and has been proved as a strong technique. Using machine learning models performed on multidimensional dataset, this article aims to find the most efficient and accurate machine learning models for tumor classification prediction.Materials & Methods: Several supervised machine learning algorithms were utilized to diagnosis and prediction of cancer tumor such as Logistic Regression Decision Tree, Random Forest and KNN. The algorithms are applied to a dataset taken from the UCI repository including 699 samples. The dataset includes Breast cancer features. To enhance the algorithms’ performance, these features are analyzed, the feature importance score and cross validation are considered. In this paper ML algorithms improved coupled by limited and selective features to produce high classification accuracy in tumor classification.Results: As a result of evaluation, Logistic Regression algorithm with accuracy value equal to 99.14%, AUC ROC equal to 99.6%, Extra Tree algorithm with accuracy value equal to 99.14% and AUC ROC equal to 99.1% have better performance than other algorithms. therefore, these techniques can be useful for diagnosis and prediction of cancer tumor and prescribe it correctly.Conclusions: The technique of machine learning can be used in medicine for analyzing the related data collections to a disease and its prediction. The area under the ROC curve and evaluating criteria related to a number of classifying algorithms of machine learning to evaluate breast cancer and indeed, the diagnosis and prediction of breast cancer is compared to determine the most appropriate classifier.
{"title":"Improvement of the Performance of Machine Learning Algorithms in Predicting Breast Cancer","authors":"Maryam Poornajaf, Sajad Yosefi","doi":"10.30699/fhi.v12i0.400","DOIUrl":"https://doi.org/10.30699/fhi.v12i0.400","url":null,"abstract":"Introduction: Breast cancer is one of the most common cancers among women compared to all other ones. Machine learning techniques can bring a large contribute on the process of prediction and early diagnosis of breast cancer, became a research hotspot and has been proved as a strong technique. Using machine learning models performed on multidimensional dataset, this article aims to find the most efficient and accurate machine learning models for tumor classification prediction.Materials & Methods: Several supervised machine learning algorithms were utilized to diagnosis and prediction of cancer tumor such as Logistic Regression Decision Tree, Random Forest and KNN. The algorithms are applied to a dataset taken from the UCI repository including 699 samples. The dataset includes Breast cancer features. To enhance the algorithms’ performance, these features are analyzed, the feature importance score and cross validation are considered. In this paper ML algorithms improved coupled by limited and selective features to produce high classification accuracy in tumor classification.Results: As a result of evaluation, Logistic Regression algorithm with accuracy value equal to 99.14%, AUC ROC equal to 99.6%, Extra Tree algorithm with accuracy value equal to 99.14% and AUC ROC equal to 99.1% have better performance than other algorithms. therefore, these techniques can be useful for diagnosis and prediction of cancer tumor and prescribe it correctly.Conclusions: The technique of machine learning can be used in medicine for analyzing the related data collections to a disease and its prediction. The area under the ROC curve and evaluating criteria related to a number of classifying algorithms of machine learning to evaluate breast cancer and indeed, the diagnosis and prediction of breast cancer is compared to determine the most appropriate classifier. ","PeriodicalId":154611,"journal":{"name":"Frontiers in Health Informatics","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116645575","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}
Pub Date : 2023-03-15DOI: 10.21203/rs.3.rs-2267767/v1
Faezeh Rahmani, F. Moghbeli, Atefeh Khoshkangin, Mohammad Reza Mazaheri Habibi
Introduction: Low levels of health literacy lead to reduced health, increased length of hospital stays, and increased use of emergency services in patients and impose higher medical costs on individuals. Considering the effect of paramedical students' health literacy on community health promotion, this study aimed to determine the level of health literacy and its associated factors in paramedical students.Material and Methods: This cross-sectional study was performed on 310 paramedical students during a two-month period from January to March 2021. The data collection tool was the Health Literacy for Iranian Adults (HELIA) questionnaire. Due to the COVID-19 pandemic, the questionnaire was designed online, and its link was provided to students.Results: Among the participants, 247 (79.7%) cases were female, and 63 (20.3%) cases were male with a mean age of 21.16 ± 1.97 years. According to the results, 3.9% of the students had inadequate health literacy, 37.3% had not so adequate health literacy, 46.6% had adequate health literacy, and 12.2% had excellent health literacy. The results of ANOVA and t-test showed a significant association between the mean total health literacy score of students and their age, gender, and semester (P <0.05).Conclusion: This study findings showed that more than half of the participating students had adequate and excellent levels of health literacy. Since paramedical students are promoters of health in the community, more attention should be paid to the education of these individuals. Therefore, it is necessary to empower them in the field of health literacy.
{"title":"Evaluation of Health Literacy and Its Associated Factors in Paramedical Students","authors":"Faezeh Rahmani, F. Moghbeli, Atefeh Khoshkangin, Mohammad Reza Mazaheri Habibi","doi":"10.21203/rs.3.rs-2267767/v1","DOIUrl":"https://doi.org/10.21203/rs.3.rs-2267767/v1","url":null,"abstract":"Introduction: Low levels of health literacy lead to reduced health, increased length of hospital stays, and increased use of emergency services in patients and impose higher medical costs on individuals. Considering the effect of paramedical students' health literacy on community health promotion, this study aimed to determine the level of health literacy and its associated factors in paramedical students.Material and Methods: This cross-sectional study was performed on 310 paramedical students during a two-month period from January to March 2021. The data collection tool was the Health Literacy for Iranian Adults (HELIA) questionnaire. Due to the COVID-19 pandemic, the questionnaire was designed online, and its link was provided to students.Results: Among the participants, 247 (79.7%) cases were female, and 63 (20.3%) cases were male with a mean age of 21.16 ± 1.97 years. According to the results, 3.9% of the students had inadequate health literacy, 37.3% had not so adequate health literacy, 46.6% had adequate health literacy, and 12.2% had excellent health literacy. The results of ANOVA and t-test showed a significant association between the mean total health literacy score of students and their age, gender, and semester (P <0.05).Conclusion: This study findings showed that more than half of the participating students had adequate and excellent levels of health literacy. Since paramedical students are promoters of health in the community, more attention should be paid to the education of these individuals. Therefore, it is necessary to empower them in the field of health literacy. ","PeriodicalId":154611,"journal":{"name":"Frontiers in Health Informatics","volume":"145 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115278408","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 literacy is an essential indicator of health care habits and consequences. Health literacy and having the right information is effective in better managing symptoms and problems and improving the overall quality of life. This systematic review aimed to analyze previous studies and collect information on multiple sclerosis patients' health literacy.Material and Methods: The PRISMA guidelines were used to define the systematic review methods. PubMed, Cochrane, Web of Science, Scopus, ScienceDirect Journal, ProQuest, Wiley Online Library, SID, and Magiran databases were searched on 14 January 2022, without restrictions in publication time. We also searched Google Scholar and Research Proposal Information System. Two independent reviewers reviewed the papers' eligibility and extract data into a spreadsheet using a structured form.Results: Of the 165 articles retrieved, 14 were eventually included in the study. All of the studies’ audiences and targets were MS patients and their families or caregivers. Four studies examined the level of health literacy of individuals. Other objectives included determining variables affecting the relationship between patients' health literacy and behaviors, comparing the effects of lecture-based teaching and peer group experience on improving patients' health literacy, and determining psychometric characteristics of the MS patient’s health literacy questionnaire. Studies assessing people's health literacy revealed that most people have an adequate or acceptable health literacy level.Conclusion: Improving the level of health literacy is one of the fundamental ways to improve the physical and mental health of MS patients to increase compliance and self-care and medication adherence. Accordingly, policymakers need to work on designing effective programs to develop health literacy and overcome the challenges associated with it.
卫生素养是卫生保健习惯和后果的重要指标。健康知识和掌握正确的信息对更好地管理症状和问题以及提高整体生活质量是有效的。本系统综述旨在分析以往关于多发性硬化症患者健康素养的研究并收集相关信息。材料和方法:采用PRISMA指南定义系统评价方法。PubMed、Cochrane、Web of Science、Scopus、ScienceDirect Journal、ProQuest、Wiley Online Library、SID和Magiran数据库于2022年1月14日检索，没有出版时间限制。我们还搜索了Google Scholar和Research Proposal Information System。两名独立审稿人审查了论文的合格性，并使用结构化表格将数据提取到电子表格中。结果:在检索到的165篇文章中，有14篇最终被纳入研究。所有研究的受众和目标都是多发性硬化症患者及其家属或照顾者。四项研究调查了个人的健康素养水平。其他目的包括确定影响患者健康素养与行为关系的变量，比较讲座式教学和同伴小组体验对提高患者健康素养的效果，确定MS患者健康素养问卷的心理测量特征。评估人们卫生素养的研究表明，大多数人具有适当或可接受的卫生素养水平。结论:提高健康素养水平是改善MS患者身心健康、提高依从性、自我保健和药物依从性的根本途径之一。因此，决策者需要致力于设计有效的方案，以发展卫生知识普及，并克服与之相关的挑战。
{"title":"The Role of Health Literacy in Multiple Sclerosis: A Systematic Review","authors":"Mahdieh Shojaei Baghini, K. Bahaadinbeigy","doi":"10.30699/fhi.v12i0.395","DOIUrl":"https://doi.org/10.30699/fhi.v12i0.395","url":null,"abstract":"Introduction: Health literacy is an essential indicator of health care habits and consequences. Health literacy and having the right information is effective in better managing symptoms and problems and improving the overall quality of life. This systematic review aimed to analyze previous studies and collect information on multiple sclerosis patients' health literacy.Material and Methods: The PRISMA guidelines were used to define the systematic review methods. PubMed, Cochrane, Web of Science, Scopus, ScienceDirect Journal, ProQuest, Wiley Online Library, SID, and Magiran databases were searched on 14 January 2022, without restrictions in publication time. We also searched Google Scholar and Research Proposal Information System. Two independent reviewers reviewed the papers' eligibility and extract data into a spreadsheet using a structured form.Results: Of the 165 articles retrieved, 14 were eventually included in the study. All of the studies’ audiences and targets were MS patients and their families or caregivers. Four studies examined the level of health literacy of individuals. Other objectives included determining variables affecting the relationship between patients' health literacy and behaviors, comparing the effects of lecture-based teaching and peer group experience on improving patients' health literacy, and determining psychometric characteristics of the MS patient’s health literacy questionnaire. Studies assessing people's health literacy revealed that most people have an adequate or acceptable health literacy level.Conclusion: Improving the level of health literacy is one of the fundamental ways to improve the physical and mental health of MS patients to increase compliance and self-care and medication adherence. Accordingly, policymakers need to work on designing effective programs to develop health literacy and overcome the challenges associated with it.","PeriodicalId":154611,"journal":{"name":"Frontiers in Health Informatics","volume":"81 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116792232","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}
Diabetes is a whole group of diseases in the body regulating blood sugar levels. There is a lack of response to the insulin produced by the pancreas. Until now, there is no definite cause to uncover the disease. If left untreated, other complications may occur so as damage to the organs in the body. The cells are not functioning very well as there is a lack of energy inside the body.
{"title":"An Introduction to Diabetes","authors":"Nur Aifiah Binti Ibrahim","doi":"10.30699/fhi.v12i0.405","DOIUrl":"https://doi.org/10.30699/fhi.v12i0.405","url":null,"abstract":"Diabetes is a whole group of diseases in the body regulating blood sugar levels. There is a lack of response to the insulin produced by the pancreas. Until now, there is no definite cause to uncover the disease. If left untreated, other complications may occur so as damage to the organs in the body. The cells are not functioning very well as there is a lack of energy inside the body.","PeriodicalId":154611,"journal":{"name":"Frontiers in Health Informatics","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121787598","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}
Nazanin Jannati, Saber Amirzadeh Googhari, Sareh Keshvardoost, A. Vaezipour, F. Zolala, S. Mehdipour, Maryam Hosseinnejad, Mozhgan Negarestani, Farhad Fatehi
Introduction: Social media platforms provide easy access to an unprecedented volume of information which could influence the awareness and perception of people during public health crises. The current study aims to explore the trends and content of the posts on Instagram.Material and Methods: We performed a retrospective content analysis of available public messages posted on Instagram. We collected data between 23 January 2020 and 25 March 2020. The inclusion criteria included an Instagram post with a hashtag related to Coronavirus (i.e. # “Corona” and # “Coronavirus”, in the Persian language). Persian hashtags were used for retrieving posts. All posts were categorized into seven categories. We performed descriptive statistics with Microsoft Excel 2019 and SPSS version 26.Results: A total of 4280 posts were extracted, out of which 1281 were categorized into seven main categories including News (n=205, 26.7%), Criticism (n=136, 17.7%), Education (n=112, 14.6%), Coronavirus’s impact on the healthcare system (n=100, 13%), Combating Coronavirus (n=98, 12.8%), Coronavirus’s impact on society (n=89, 11.6%), Joke (n=28, 3.6%).Conclusion:Our findings revealed that the trend of posts on social media was influenced by factors such as the nature of the information sources as well as social and political occasions. This study provides insight into health dissemination on social media for future responses to public health crises.
{"title":"COVID-19 Information Dissemination Via Social Media: Content Analysis of Instagram Posts During the COVID-19 Outbreak","authors":"Nazanin Jannati, Saber Amirzadeh Googhari, Sareh Keshvardoost, A. Vaezipour, F. Zolala, S. Mehdipour, Maryam Hosseinnejad, Mozhgan Negarestani, Farhad Fatehi","doi":"10.30699/fhi.v12i0.398","DOIUrl":"https://doi.org/10.30699/fhi.v12i0.398","url":null,"abstract":"Introduction: Social media platforms provide easy access to an unprecedented volume of information which could influence the awareness and perception of people during public health crises. The current study aims to explore the trends and content of the posts on Instagram.Material and Methods: We performed a retrospective content analysis of available public messages posted on Instagram. We collected data between 23 January 2020 and 25 March 2020. The inclusion criteria included an Instagram post with a hashtag related to Coronavirus (i.e. # “Corona” and # “Coronavirus”, in the Persian language). Persian hashtags were used for retrieving posts. All posts were categorized into seven categories. We performed descriptive statistics with Microsoft Excel 2019 and SPSS version 26.Results: A total of 4280 posts were extracted, out of which 1281 were categorized into seven main categories including News (n=205, 26.7%), Criticism (n=136, 17.7%), Education (n=112, 14.6%), Coronavirus’s impact on the healthcare system (n=100, 13%), Combating Coronavirus (n=98, 12.8%), Coronavirus’s impact on society (n=89, 11.6%), Joke (n=28, 3.6%).Conclusion:Our findings revealed that the trend of posts on social media was influenced by factors such as the nature of the information sources as well as social and political occasions. This study provides insight into health dissemination on social media for future responses to public health crises.","PeriodicalId":154611,"journal":{"name":"Frontiers in Health Informatics","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122654159","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: Universities are the origin of society's transformations in various fields and students as the main pillars of the university form the main body of various organizations and organs of the society. For this purpose, it is necessary to have information about the current situation and the attitude of students towards their field. This study was conducted with the aim of investigating the effective factors in the selection of nutrition science students of Varastegan Institute for Medical Sciences.Material and Methods: This is an applied study that was carried out in a descriptive-cross-sectional way. The studied population was students studying nutrition sciences at Varastegan Institute for Medical Sciences. To collect data, a questionnaire was created by a researcher, whose validity was evaluated with the help of expert panels consisting of experts in the health information technology group of Varastegan Institute for Medical Sciences, and the reliability of the questionnaire was determined by determining Cronbach's alpha.Results: According to the findings of the study, the majority of users were 68.7% female and 31.3% male. 43.3% of students had an average knowledge and awareness of their field and 44.8% had a positive view of their field. 8/ 38% of students chose this field based on the recommendation of others. The satisfaction with the field of study of the current study was 49.3%, which was close to the satisfaction of half of the students under study, and 61.2% of the students were very satisfied with the assignment of medical system code and having an office. 41.8% of nutrition science students were very satisfied with their career future and 41% believe in the existence of a suitable job market.Conclusion: The most important factor in choosing a field is the assignment of the code of the medical system and having an office at the time of employment, and many students believe that this field is suitable for social values and the existence of a suitable job market, and they consider the relevant job interesting and purposeful to serve the society.
{"title":"Investigation Factors Affecting Academic Tendency in Bachelor Students of Nutrition Sciences of Varastegan Institute for Medical Sciences: 2022","authors":"G. Moradi, Mahsasadat Hamouni, F. Moghbeli","doi":"10.30699/fhi.v12i0.397","DOIUrl":"https://doi.org/10.30699/fhi.v12i0.397","url":null,"abstract":"Introduction: Universities are the origin of society's transformations in various fields and students as the main pillars of the university form the main body of various organizations and organs of the society. For this purpose, it is necessary to have information about the current situation and the attitude of students towards their field. This study was conducted with the aim of investigating the effective factors in the selection of nutrition science students of Varastegan Institute for Medical Sciences.Material and Methods: This is an applied study that was carried out in a descriptive-cross-sectional way. The studied population was students studying nutrition sciences at Varastegan Institute for Medical Sciences. To collect data, a questionnaire was created by a researcher, whose validity was evaluated with the help of expert panels consisting of experts in the health information technology group of Varastegan Institute for Medical Sciences, and the reliability of the questionnaire was determined by determining Cronbach's alpha.Results: According to the findings of the study, the majority of users were 68.7% female and 31.3% male. 43.3% of students had an average knowledge and awareness of their field and 44.8% had a positive view of their field. 8/ 38% of students chose this field based on the recommendation of others. The satisfaction with the field of study of the current study was 49.3%, which was close to the satisfaction of half of the students under study, and 61.2% of the students were very satisfied with the assignment of medical system code and having an office. 41.8% of nutrition science students were very satisfied with their career future and 41% believe in the existence of a suitable job market.Conclusion: The most important factor in choosing a field is the assignment of the code of the medical system and having an office at the time of employment, and many students believe that this field is suitable for social values and the existence of a suitable job market, and they consider the relevant job interesting and purposeful to serve the society.","PeriodicalId":154611,"journal":{"name":"Frontiers in Health Informatics","volume":"134 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117304412","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: Artificial intelligence has been changing the way healthcare has been provided in many high-risk environments or areas with poor healthcare facilities. The emergence of epidemics and new diseases, as well as the crucial role of early diagnosis in prevention and the adoption of more effective treatments have highlighted the need for accurate design and self-organization of Clinical Decision Support Systems (CDSSs).Material and Methods: In this study, a CDSS based on a neural networks (NN) and genetic algorithm is proposed. Since, on the one hand, the performance of the neural network (NN) is highly dependent on its parameters, and on the other hand, there is a constant need for optimization experts to fine-tune the parameters in the use of new data, a new chromosomal structure is proposed to automatically extract the optimal NN architecture, the number of layers and neurons. The goal is to increase the reusability of the model and ease of use by health experts.Results: To evaluate the performance of the model, two standard breast cancer (BC) datasets, WBC and WDBC, were used. The model uses 70% of the data set for training and the remaining equally used for evaluation and testing. The test accuracy of the proposed model on WBC and WDBC datasets was 98.51 and 97.55%, respectively. The optimal NN architecture on WBC consisted a three-hidden layers with 18, 15 and 19 neurons in each layers, and on WDBC consisted one hidden layer with a single neuron.Conclusion: The proposed chromosomal structure is able to derive optimal NN architecture. In according to the high classification accuracy of the model in the diagnosis of BC and providing the different architectures in accordance with the hardware implementation considerations, the proposed model can be used effectively in the diagnosis of other diseases.
{"title":"A Decision Support System Based on Neural Network and Genetic Algorithm: Case Study of Breast Cancer","authors":"F. Ahouz, A. Bastani, Amin Golabpour","doi":"10.30699/fhi.v11i1.375","DOIUrl":"https://doi.org/10.30699/fhi.v11i1.375","url":null,"abstract":"Introduction: Artificial intelligence has been changing the way healthcare has been provided in many high-risk environments or areas with poor healthcare facilities. The emergence of epidemics and new diseases, as well as the crucial role of early diagnosis in prevention and the adoption of more effective treatments have highlighted the need for accurate design and self-organization of Clinical Decision Support Systems (CDSSs).Material and Methods: In this study, a CDSS based on a neural networks (NN) and genetic algorithm is proposed. Since, on the one hand, the performance of the neural network (NN) is highly dependent on its parameters, and on the other hand, there is a constant need for optimization experts to fine-tune the parameters in the use of new data, a new chromosomal structure is proposed to automatically extract the optimal NN architecture, the number of layers and neurons. The goal is to increase the reusability of the model and ease of use by health experts.Results: To evaluate the performance of the model, two standard breast cancer (BC) datasets, WBC and WDBC, were used. The model uses 70% of the data set for training and the remaining equally used for evaluation and testing. The test accuracy of the proposed model on WBC and WDBC datasets was 98.51 and 97.55%, respectively. The optimal NN architecture on WBC consisted a three-hidden layers with 18, 15 and 19 neurons in each layers, and on WDBC consisted one hidden layer with a single neuron.Conclusion: The proposed chromosomal structure is able to derive optimal NN architecture. In according to the high classification accuracy of the model in the diagnosis of BC and providing the different architectures in accordance with the hardware implementation considerations, the proposed model can be used effectively in the diagnosis of other diseases.","PeriodicalId":154611,"journal":{"name":"Frontiers in Health Informatics","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115841478","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}
Houshang Rafat Panah Bayegi, L. Jarahi, Milad Mahmoudabadi, M. Sarbaz, Seyyedeh Fatemeh Mousavi Baigi, Khalil Kimiafar
Introduction: Human T-cell lymphotropic virus type 1 (HTLV-1) is known to be endemic in the population of northeastern Iran. This study was conducted with the aim of investigating the knowledge and attitude of medical students of Mashhad University of Medical Sciences about the HTLV-1 virus.Material and Methods: The present study was a descriptive-analytical study that was conducted in Mashhad Medical School from April to June 2014. The research population included all medical students studying at the time of the study (307 people). The tool of data collection was a questionnaire including 4 parts of demographic characteristics, the amount of information resources used, the level of awareness about HTLV-1 infection and measuring the attitude of students towards HTLV-1 infection. The data was analyzed in the form of descriptive statistics using SPSS 16.0 software.Results: A total of 271 people responded to the questionnaire (response rate: 88/27). Among the participants, 130 were male and 141 were female. The majority of students, 161 people got their information from the classroom and 157 people were natives of Mashhad. The information obtained from the description of the questions and the percentage of correct answers to the questions showed that the level of students' knowledge about this infection was average with an average score of 16.66 out of 40 points, and the average score of the students' attitude was reported as 68.11 with an average level.Conclusion: The obtained results reported the level of knowledge of the target group as medium-low, and the level of attitude of this group as medium-high. Also, there was a direct relationship between the amount of information and the level of attitude with the year of entering the university and studying in the university, which reports the slope of this change as low.
{"title":"Assess the Knowledge of Medical Students About HTLV-1 in Mashhad University of Medical Science","authors":"Houshang Rafat Panah Bayegi, L. Jarahi, Milad Mahmoudabadi, M. Sarbaz, Seyyedeh Fatemeh Mousavi Baigi, Khalil Kimiafar","doi":"10.30699/fhi.v11i1.394","DOIUrl":"https://doi.org/10.30699/fhi.v11i1.394","url":null,"abstract":"Introduction: Human T-cell lymphotropic virus type 1 (HTLV-1) is known to be endemic in the population of northeastern Iran. This study was conducted with the aim of investigating the knowledge and attitude of medical students of Mashhad University of Medical Sciences about the HTLV-1 virus.Material and Methods: The present study was a descriptive-analytical study that was conducted in Mashhad Medical School from April to June 2014. The research population included all medical students studying at the time of the study (307 people). The tool of data collection was a questionnaire including 4 parts of demographic characteristics, the amount of information resources used, the level of awareness about HTLV-1 infection and measuring the attitude of students towards HTLV-1 infection. The data was analyzed in the form of descriptive statistics using SPSS 16.0 software.Results: A total of 271 people responded to the questionnaire (response rate: 88/27). Among the participants, 130 were male and 141 were female. The majority of students, 161 people got their information from the classroom and 157 people were natives of Mashhad. The information obtained from the description of the questions and the percentage of correct answers to the questions showed that the level of students' knowledge about this infection was average with an average score of 16.66 out of 40 points, and the average score of the students' attitude was reported as 68.11 with an average level.Conclusion: The obtained results reported the level of knowledge of the target group as medium-low, and the level of attitude of this group as medium-high. Also, there was a direct relationship between the amount of information and the level of attitude with the year of entering the university and studying in the university, which reports the slope of this change as low.","PeriodicalId":154611,"journal":{"name":"Frontiers in Health Informatics","volume":"1247 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131074009","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}
Seyyedeh Fatemeh Mousavi Baigi, Masomeh Sarbaz, D. Sobhani-Rad, A. Mousavi, Khalil Kimiafar
Introduction: In recent decades, following the upward trend of aging, one out of three people in the world need rehabilitation services during the period of illness or injury. Considering the long-term complications and high costs of treatment, the need to follow up and review the evidence to find the best care programs and extensive planning in this field seems mandatory. Registry systems (registration) in this area can provide the necessary evidence for strategic decisions in this field. Of course, launching and developing these systems comes with challenges. Therefore, the purpose of this comprehensive literature review is to examine the challenges and benefits of developing a rehabilitation registration system.Materials and Method: A systematic review, in studies published in English, without time limit and by searching for keywords in the keywords, title and abstract of reliable scientific databases Web of Science, Scopus, PubMed and Science Direct, as well as searching the title of studies in the database Cochrane data was accessed on March 31, 2021. Studies that were a possible answer to the researched question based on the title and content were examined. A total of 1924 related studies were identified; And finally, 32 qualified articles were included in this review.Results: One of the most important challenges investigated was the limitation of rehabilitation comprehensive registration systems. Other challenges include the lack of support for ensuring the quality of registration data, insufficient funds for investment, privacy and data security, the unclear purpose of registration system development, access to hardware infrastructure, lack of binding laws and regulations related to registration systems, lack of access to sufficient information. To implement information registration systems, continuous monitoring and holding training courses.Conclusion: The most important challenge investigated was that currently the health care and rehabilitation registration systems around the world are focused on single diseases (single discipline rehabilitation), which does not meet the needs of patients due to the multifactorial nature of rehabilitation services and chronic diseases. Therefore, it seems that the connection between the data registration systems with the help of a comprehensive guideline or model or the creation of a national integrated central database in the form of integration with other health information systems and based on electronic health records will be very efficient.
引言:近几十年来，随着人口老龄化的上升趋势，世界上每三个人中就有一个人在患病或受伤期间需要康复服务。考虑到长期的并发症和高昂的治疗费用，需要跟进和审查证据，以找到最好的护理方案和广泛的规划，在这一领域似乎是必要的。该领域的注册系统(注册)可以为该领域的战略决策提供必要的证据。当然，发射和开发这些系统伴随着挑战。因此，本综合文献综述的目的是研究发展康复登记制度的挑战和好处。材料与方法:对发表于英文的研究进行系统综述，不受时间限制，通过在可靠的科学数据库Web of Science、Scopus、PubMed和Science Direct的关键词、标题和摘要中搜索关键词，以及在数据库中搜索研究标题，检索Cochrane数据，检索时间为2021年3月31日。根据标题和内容，对可能回答所研究问题的研究进行了检查。共确定了1924项相关研究;最终，32篇符合条件的文章被纳入本综述。结果:康复综合登记系统的局限性是调查中最重要的挑战之一。其他挑战包括缺乏对确保注册数据质量的支持、投资资金不足、隐私和数据安全、注册系统开发的目的不明确、硬件基础设施的获取、缺乏与注册系统相关的具有约束力的法律和法规、缺乏获得足够信息的途径。实施信息登记制度，持续监测和举办培训课程。结论:目前世界各国的卫生保健和康复登记制度主要集中于单一疾病(单一学科康复)，由于康复服务和慢性病的多因素性质，不能满足患者的需求。因此，借助综合指南或模型将数据登记系统连接起来，或以与其他卫生信息系统集成的形式建立一个基于电子健康记录的国家综合中央数据库，似乎将非常有效。
{"title":"Rehabilitation Registration Systems: Current Recommendations and Challenges","authors":"Seyyedeh Fatemeh Mousavi Baigi, Masomeh Sarbaz, D. Sobhani-Rad, A. Mousavi, Khalil Kimiafar","doi":"10.30699/fhi.v11i1.388","DOIUrl":"https://doi.org/10.30699/fhi.v11i1.388","url":null,"abstract":"Introduction: In recent decades, following the upward trend of aging, one out of three people in the world need rehabilitation services during the period of illness or injury. Considering the long-term complications and high costs of treatment, the need to follow up and review the evidence to find the best care programs and extensive planning in this field seems mandatory. Registry systems (registration) in this area can provide the necessary evidence for strategic decisions in this field. Of course, launching and developing these systems comes with challenges. Therefore, the purpose of this comprehensive literature review is to examine the challenges and benefits of developing a rehabilitation registration system.Materials and Method: A systematic review, in studies published in English, without time limit and by searching for keywords in the keywords, title and abstract of reliable scientific databases Web of Science, Scopus, PubMed and Science Direct, as well as searching the title of studies in the database Cochrane data was accessed on March 31, 2021. Studies that were a possible answer to the researched question based on the title and content were examined. A total of 1924 related studies were identified; And finally, 32 qualified articles were included in this review.Results: One of the most important challenges investigated was the limitation of rehabilitation comprehensive registration systems. Other challenges include the lack of support for ensuring the quality of registration data, insufficient funds for investment, privacy and data security, the unclear purpose of registration system development, access to hardware infrastructure, lack of binding laws and regulations related to registration systems, lack of access to sufficient information. To implement information registration systems, continuous monitoring and holding training courses.Conclusion: The most important challenge investigated was that currently the health care and rehabilitation registration systems around the world are focused on single diseases (single discipline rehabilitation), which does not meet the needs of patients due to the multifactorial nature of rehabilitation services and chronic diseases. Therefore, it seems that the connection between the data registration systems with the help of a comprehensive guideline or model or the creation of a national integrated central database in the form of integration with other health information systems and based on electronic health records will be very efficient.","PeriodicalId":154611,"journal":{"name":"Frontiers in Health Informatics","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127501265","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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