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Int. J. E Health Medical Commun.最新文献

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Utilization of Transfer Learning Model in Detecting COVID-19 Cases From Chest X-Ray Images 迁移学习模型在胸部x线图像COVID-19病例检测中的应用
Int. J. E Health Medical Commun. Pub Date : 2022-07-01 DOI: 10.4018/IJEHMC.20220701.oa2
M. Jawahar, L. Anbarasi, Prassanna Jayachandran, Manikandan Ramachandran, F. Al-turjman
{"title":"Utilization of Transfer Learning Model in Detecting COVID-19 Cases From Chest X-Ray Images","authors":"M. Jawahar, L. Anbarasi, Prassanna Jayachandran, Manikandan Ramachandran, F. Al-turjman","doi":"10.4018/IJEHMC.20220701.oa2","DOIUrl":"https://doi.org/10.4018/IJEHMC.20220701.oa2","url":null,"abstract":"Diagnosis of COVID-19 pneumonia using patients’ chest X-Ray images is new but yet important task in the field of medicine. Researchers from different parts of the globe have developed many deep learning models to classify COVID-19. The performance of feature extraction and classifier plays a vital role in the recognizing the different patterns in the image. The pivotal process is the extraction of optimum features from the chest X-Ray images. The main goal of this study is to design an efficient hybrid algorithm that integrates the robustness of MobileNet (using transfer learning approach) to extract features and Support Vector Machine (SVM) to classify COVID-19. Experiments were conducted to test the proposed algorithm and it was found to have a high classification accuracy of 95%.","PeriodicalId":375617,"journal":{"name":"Int. J. E Health Medical Commun.","volume":"55 17","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120839659","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}
引用次数: 9
Comparison of Active COVID-19 Cases per Population Using Time-Series Models 使用时间序列模型比较每个人群的COVID-19活动性病例
Int. J. E Health Medical Commun. Pub Date : 2022-07-01 DOI: 10.4018/ijehmc.20220701.oa6
S. Folorunso, J. B. Awotunde, O. Banjo, E. Ogundepo, N. Adeboye
{"title":"Comparison of Active COVID-19 Cases per Population Using Time-Series Models","authors":"S. Folorunso, J. B. Awotunde, O. Banjo, E. Ogundepo, N. Adeboye","doi":"10.4018/ijehmc.20220701.oa6","DOIUrl":"https://doi.org/10.4018/ijehmc.20220701.oa6","url":null,"abstract":"This research explored the precision of diverse time-series models for COVID-19 epidemic detection in all the thirty-six different states and the Federal Capital Territory (FCT) in Nigeria with the maximum count of daily cumulative of confirmed, recovered and death cases as of 4 November 2020 of COVID-19 and populace of each state. A 14-multi step ahead forecast system for active coronavirus cases was built, analyzed and compared for six (6) different deep learning-stimulated and statistical time-series models using two openly accessible datasets. The results obtained showed that based on RMSE metric, ARIMA model obtained the best values for four of the states (0.002537, 0.001969.12E-058, 5.36E-05 values for Lagos, FCT, Edo and Delta states respectively). While no method is all-encompassing for predicting daily active coronavirus cases for different states in Nigeria, ARIMA model obtains the highest-ranking prediction performance and attained a good position results in other states.","PeriodicalId":375617,"journal":{"name":"Int. J. E Health Medical Commun.","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124985724","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}
引用次数: 0
Combating Drug Counterfeiting by Tracing Ownership Transfer Using Blockchain Technology 利用区块链技术追踪所有权转移，打击假药
Int. J. E Health Medical Commun. Pub Date : 2022-01-01 DOI: 10.4018/ijehmc.309429
V. Bali, Tejaswi Khanna, Pawan Soni, Shivam Gupta, Shivi Chauhan, Shivani Gupta
{"title":"Combating Drug Counterfeiting by Tracing Ownership Transfer Using Blockchain Technology","authors":"V. Bali, Tejaswi Khanna, Pawan Soni, Shivam Gupta, Shivi Chauhan, Shivani Gupta","doi":"10.4018/ijehmc.309429","DOIUrl":"https://doi.org/10.4018/ijehmc.309429","url":null,"abstract":"Supply chain management in healthcare sector plays significant role in the lives of people. Presence of intermediaries and lack of traceability has lured it towards drug counterfeiting, which reduces drug efficacy, thus hampering patients' trust and putting their lives in danger. Blockchain has emerged as a groundbreaking technology which provide a system that is immutable and transparent without the requirement of a trusted third party. This paper depicts how blockchain can provide a solution to reduce drug counterfeit in the pharmaceutical supply chain. This is achieved by creating a Blockchain Network in which each participant and the drug is registered to maintain transparency of transactions among all the participants. Realtime transfer of ownership in the blockchain creates all-round visibility among the registered participants to retrieve information like the current owner, timestamp of ownership transfer and authenticity of drugs. This paper implements PharmaChain for real-time traceability and trackability information of drugs from end-to-end of the pharmaceutical supply chain.","PeriodicalId":375617,"journal":{"name":"Int. J. E Health Medical Commun.","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115434441","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}
引用次数: 2
Meal Planning for Alzheimer's Disease Using an Ontology-Assisted Multiple Criteria Decision-Making Approach 使用本体辅助的多标准决策方法进行阿尔茨海默病膳食计划
Int. J. E Health Medical Commun. Pub Date : 2022-01-01 DOI: 10.4018/ijehmc.316133
M. Amiri, Juan Li, Souradip Roy
{"title":"Meal Planning for Alzheimer's Disease Using an Ontology-Assisted Multiple Criteria Decision-Making Approach","authors":"M. Amiri, Juan Li, Souradip Roy","doi":"10.4018/ijehmc.316133","DOIUrl":"https://doi.org/10.4018/ijehmc.316133","url":null,"abstract":"As healthy diets and nutrition are crucial for people with Alzheimer's disease (AD), caregivers of patients with AD need to provide a balanced diet with the correct nutrients to boost the health and well-being of patients. However, this is challenging as they are likely to suffer from aging-related problems (such as teeth or gum problems) that make eating more uncomfortable; the planners, who are usually patients' family members, generally face high pressure, a busy schedule, and little experience. To help unprofessional caregivers of AD plan meals with the right nutrition and flavors, in this paper, the authors propose a meal planning mechanism that uses a multiple criteria decision-making approach to integrate various factors that affect a caregiver's choice of meals for AD patients. Ontology-based knowledge has been used to model personal preferences and characteristics and customize general diet recommendations. Case studies have demonstrated the feasibility and usability of the proposed approach.","PeriodicalId":375617,"journal":{"name":"Int. J. E Health Medical Commun.","volume":"82 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121603388","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}
引用次数: 0
Investigating the Receptiveness Attitude of the Patient With Diabetes Retinopathy Towards the Use of Teleophthalmology 糖尿病视网膜病变患者对远程眼科手术接受态度的调查
Int. J. E Health Medical Commun. Pub Date : 2022-01-01 DOI: 10.4018/ijehmc.309685
Chiemelie Benneth Iloka, Idongesit Aniekan Ekpo, Husam Rjoub, K. Iyiola, J. A. Odugbesan
{"title":"Investigating the Receptiveness Attitude of the Patient With Diabetes Retinopathy Towards the Use of Teleophthalmology","authors":"Chiemelie Benneth Iloka, Idongesit Aniekan Ekpo, Husam Rjoub, K. Iyiola, J. A. Odugbesan","doi":"10.4018/ijehmc.309685","DOIUrl":"https://doi.org/10.4018/ijehmc.309685","url":null,"abstract":"Research on the attitude of diabetes retinopathy's (DR) patients towards teleophthalmology as a branch of telemedicine has not been examined in developing countries. This article examines the receptiveness attitude of the patients with DR towards the use of teleophthalmology using 400 questionnaires to examine patients in Calabar DR screening center in Cross River State, Nigeria. The hypotheses were tested using multiple indicators multiple causes (MIMIC) as a special case of the structural equation modeling (SEM). The findings in this study indicated high cost and excess time negatively affects patient attitude, information, knowledge, and experience significantly and positively predict patients attitude towards teleophthalmology. Furthermore, the result of the paper shows that convenience and knowledge for 35.7 percent of the receptiveness of patients towards teleophthalmology. This study contributes by identifying that among other factors positive factors to enhance patient's receptive attitude to being diagnosis with diabetes retinopathy through telemedicine.","PeriodicalId":375617,"journal":{"name":"Int. J. E Health Medical Commun.","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124893093","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}
引用次数: 0
WhatsApp and Health Communication: Its Impact on Promoting Children's Oral Healthcare Among Parents WhatsApp与健康传播:对家长促进儿童口腔健康的影响
Int. J. E Health Medical Commun. Pub Date : 2022-01-01 DOI: 10.4018/ijehmc.315127
Siti Ezaleila Mustafa, Nor Zaliza Sarmiti, Z. Yusof, Norazana Mohd Nor, Mariani Md Nor
{"title":"WhatsApp and Health Communication: Its Impact on Promoting Children's Oral Healthcare Among Parents","authors":"Siti Ezaleila Mustafa, Nor Zaliza Sarmiti, Z. Yusof, Norazana Mohd Nor, Mariani Md Nor","doi":"10.4018/ijehmc.315127","DOIUrl":"https://doi.org/10.4018/ijehmc.315127","url":null,"abstract":"Little is known about the use of WhatsApp in promoting oral health among parents or caregivers. Therefore, the survey examined the impact of social media in disseminating health infographic messages in supporting children's oral health from the parent's perspective. The group of respondents read or saw posts or messages related to health education through Facebook (n=85, 31.9%), WhatsApp (n=68, 25.2%), and YouTube (n=61, 22.6%). There was a significant difference before and after the infographics were sent to the respondent, and it was found to be statistically significant (P-value <0.001). As a social media platform for oral health education purposes, WhatsApp appeared to improve parents' knowledge and behaviors towards their children's oral health. Most respondents perceived WhatsApp to be beneficial. Knowing how people use social media now could help health communication efforts be more effective and equitable.","PeriodicalId":375617,"journal":{"name":"Int. J. E Health Medical Commun.","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127676198","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}
引用次数: 0
ADDietCoach: A Personalized Virtual Diet Coach for Alzheimer's Disease addetcoach:阿尔茨海默病个性化虚拟饮食教练
Int. J. E Health Medical Commun. Pub Date : 2021-11-01 DOI: 10.4018/IJEHMC.20211101.OA6
Rasha Hendawi, Juan Li, Shadi Alian
{"title":"ADDietCoach: A Personalized Virtual Diet Coach for Alzheimer's Disease","authors":"Rasha Hendawi, Juan Li, Shadi Alian","doi":"10.4018/IJEHMC.20211101.OA6","DOIUrl":"https://doi.org/10.4018/IJEHMC.20211101.OA6","url":null,"abstract":"The aging population worldwide is expected to increase the prevalence of Alzheimer’s disease. As there is no medical curative treatment for this disease to date, alternative treatments have been applied to improve the patient’s brain and general health. One of these efforts includes providing Alzheimer’s patients with proper food and nutrition. In this paper, the authors propose a knowledge-powered personalized virtual coach to provide diet and nutrition assistance to patients of Alzheimer’s and/ or their informal caregivers. The virtual coach is built on top of an ontology-enhanced knowledge base containing knowledge about patients, Alzheimer’s disease, food, and nutrition. Semantics-based searching and reasoning are performed on the knowledge base to get personalized context-aware recommendation and education about healthy eating for Alzheimer’s patients. The proposed system has been implemented as a mobile application. Evaluation based on use cases has demonstrated the usefulness of this tool.","PeriodicalId":375617,"journal":{"name":"Int. J. E Health Medical Commun.","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131218252","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}
引用次数: 0
Basic Study on Scale-Free Networks and Targeted Antivirus Prophylaxis Supported by Information Communication Tools 信息通信工具支持的无标度网络及针对性防病毒预防基础研究
Int. J. E Health Medical Commun. Pub Date : 2021-11-01 DOI: 10.4018/IJEHMC.287587
I. Nakajima, Kiyoshi Kurokawa, S. Morita, Y. Nakagawa
{"title":"Basic Study on Scale-Free Networks and Targeted Antivirus Prophylaxis Supported by Information Communication Tools","authors":"I. Nakajima, Kiyoshi Kurokawa, S. Morita, Y. Nakagawa","doi":"10.4018/IJEHMC.287587","DOIUrl":"https://doi.org/10.4018/IJEHMC.287587","url":null,"abstract":"","PeriodicalId":375617,"journal":{"name":"Int. J. E Health Medical Commun.","volume":"49 5","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132783040","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}
引用次数: 1
Performance Evaluation of Different Machine Learning Classification Algorithms for Disease Diagnosis 不同机器学习分类算法在疾病诊断中的性能评价
Int. J. E Health Medical Commun. Pub Date : 2021-11-01 DOI: 10.4018/IJEHMC.20211101.OA5
Munder Al-Hashem, Ali Mohammad Alqudah, Q. Qananwah
{"title":"Performance Evaluation of Different Machine Learning Classification Algorithms for Disease Diagnosis","authors":"Munder Al-Hashem, Ali Mohammad Alqudah, Q. Qananwah","doi":"10.4018/IJEHMC.20211101.OA5","DOIUrl":"https://doi.org/10.4018/IJEHMC.20211101.OA5","url":null,"abstract":"","PeriodicalId":375617,"journal":{"name":"Int. J. E Health Medical Commun.","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133846171","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}
引用次数: 9
Activity Recognition From Smartphone Data Using WSVM-HMM Classification 基于WSVM-HMM分类的智能手机活动识别
Int. J. E Health Medical Commun. Pub Date : 2021-11-01 DOI: 10.4018/ijehmc.20211101.oa11
M. Abidine, B. Fergani
{"title":"Activity Recognition From Smartphone Data Using WSVM-HMM Classification","authors":"M. Abidine, B. Fergani","doi":"10.4018/ijehmc.20211101.oa11","DOIUrl":"https://doi.org/10.4018/ijehmc.20211101.oa11","url":null,"abstract":"A lot of real-life mobile sensing applications are becoming available nowadays. The traditional approach for activity recognition employs machine learning algorithms to learn from collected data from smartphpne and induce a model. The model generation is usually performed offline on a server system and later deployed to the phone for activity recognition. In this paper, we propose a new hybrid classification model to perform automatic recognition of activities using built-in embedded sensors present in smartphones. The proposed method uses a trick to classify the ongoing activity by combining Weighted Support Vector Machines (WSVM) model and Hidden Markov Model (HMM) model. The sensory inputs to the classifier are reduced with the Linear Discriminant Analysis (LDA). We demonstrate how to train the hybrid approach in this setting, introduce an adaptive regularization parameter for WSVM approach, and illustrate how our proposed method outperforms the state-of-the-art on a large benchmark dataset.","PeriodicalId":375617,"journal":{"name":"Int. J. E Health Medical Commun.","volume":"247 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127537512","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}
引用次数: 0
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