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Int. J. E Health Medical Commun.最新文献

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Validation of Performance Homogeneity of Chan-Vese Model on Selected Tumour Cells Chan-Vese模型在肿瘤细胞上的性能均匀性验证
Int. J. E Health Medical Commun. Pub Date : 2021-11-01 DOI: 10.4018/IJEHMC.20211101.OA7
J. K. Appati, Franklin Iron Badzi, M. Soli, Stephane Jnr Nwolley, Ismail Wafaa Denwar
{"title":"Validation of Performance Homogeneity of Chan-Vese Model on Selected Tumour Cells","authors":"J. K. Appati, Franklin Iron Badzi, M. Soli, Stephane Jnr Nwolley, Ismail Wafaa Denwar","doi":"10.4018/IJEHMC.20211101.OA7","DOIUrl":"https://doi.org/10.4018/IJEHMC.20211101.OA7","url":null,"abstract":"","PeriodicalId":375617,"journal":{"name":"Int. J. E Health Medical Commun.","volume":"386 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":"131458625","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
Artificial Intelligence-Empowered Chatbot for Effective COVID-19 Information Delivery to Older Adults 利用人工智能聊天机器人向老年人有效传递COVID-19信息
Int. J. E Health Medical Commun. Pub Date : 2021-11-01 DOI: 10.4018/ijehmc.293285
Xin Wang, Tianyi Liang, Juan Li, Souradip Roy, Vikram Pandey, Yang Du, Jun Kong
{"title":"Artificial Intelligence-Empowered Chatbot for Effective COVID-19 Information Delivery to Older Adults","authors":"Xin Wang, Tianyi Liang, Juan Li, Souradip Roy, Vikram Pandey, Yang Du, Jun Kong","doi":"10.4018/ijehmc.293285","DOIUrl":"https://doi.org/10.4018/ijehmc.293285","url":null,"abstract":"The coronavirus disease 2019 (COVID-19) epidemic poses a threat to the everyday life of people worldwide and brings challenges to the global health system. During this outbreak, it is critical to find creative ways to extend the reach of informatics into every person in society. Although there are many websites and mobile applications for this purpose, they are insufficient in reaching vulnerable populations like older adults who are not familiar with using new technologies to access information. In this paper, we propose an AI-enabled chatbot assistant that delivers real-time, useful, context-aware, and personalized information about COVID-19 to users, especially older adults. To use the assistant, a user simply speaks to it through a mobile phone or a smart speaker. This natural and interactive interface does not require the user to have any technical background. The virtual assistant was evaluated in the lab environment through various types of use cases. Preliminary qualitative test results demonstrate a reasonable precision and recall rate.","PeriodicalId":375617,"journal":{"name":"Int. J. E Health Medical Commun.","volume":"81 2-3 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":"123457672","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
An Ensemble Random Forest Algorithm for Privacy Preserving Distributed Medical Data Mining 一种保护隐私的分布式医疗数据挖掘集成随机森林算法
Int. J. E Health Medical Commun. Pub Date : 2021-11-01 DOI: 10.4018/IJEHMC.20211101.OA8
Musavir Hassan, M. A. Butt, Majid Zaman
{"title":"An Ensemble Random Forest Algorithm for Privacy Preserving Distributed Medical Data Mining","authors":"Musavir Hassan, M. A. Butt, Majid Zaman","doi":"10.4018/IJEHMC.20211101.OA8","DOIUrl":"https://doi.org/10.4018/IJEHMC.20211101.OA8","url":null,"abstract":"","PeriodicalId":375617,"journal":{"name":"Int. J. E Health Medical Commun.","volume":"235 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":"122957608","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
EMG-Based Essential Tremor Detection Using PSD Features With Recurrent Feedforward Back Propogation Neural Network 基于PSD特征的递归前馈反传播神经网络肌电特发性震颤检测
Int. J. E Health Medical Commun. Pub Date : 2021-11-01 DOI: 10.4018/ijehmc.20211101.oa10
N. Sriraam
{"title":"EMG-Based Essential Tremor Detection Using PSD Features With Recurrent Feedforward Back Propogation Neural Network","authors":"N. Sriraam","doi":"10.4018/ijehmc.20211101.oa10","DOIUrl":"https://doi.org/10.4018/ijehmc.20211101.oa10","url":null,"abstract":"Essential tremors (ET) are slow progressive neurological disorder that reduces muscular movements and involuntary muscular contractions. The further complications of ET may lead to Parkinson’s disease and therefore it is very crucial to identify at the early onset. This research study deals with the identification of the presence of ET from the EMG of the patient by using power spectral density (PSD) features. Several PSD estimation methods such as Welch, Yule Walker, covariance, modified covariance, Eigen Vector based on Eigen value and MUSIC, and Thompson Multitaper are employed and are then classified using a recurrent feedback Elman neural network (RFBEN). It is observed from the experimental results that the MUSIC method of estimating the PSD of the EMG along with RFBEN classifier yields a classification accuracy of 99.81%. It can be concluded that the proposed approach demonstrates the possibility of developing automated computer aided diagnostic tool for early detection of Essential tremors.","PeriodicalId":375617,"journal":{"name":"Int. J. E Health Medical Commun.","volume":"24 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":"129331705","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
Semantic Segmentation of Hippocampal Subregions With U-Net Architecture 基于U-Net结构的海马亚区语义分割
Int. J. E Health Medical Commun. Pub Date : 2021-11-01 DOI: 10.4018/IJEHMC.20211101.OA4
Soraya Nasser, Moulkheir Naoui, Ghalem Belalem, S. Mahmoudi
{"title":"Semantic Segmentation of Hippocampal Subregions With U-Net Architecture","authors":"Soraya Nasser, Moulkheir Naoui, Ghalem Belalem, S. Mahmoudi","doi":"10.4018/IJEHMC.20211101.OA4","DOIUrl":"https://doi.org/10.4018/IJEHMC.20211101.OA4","url":null,"abstract":"","PeriodicalId":375617,"journal":{"name":"Int. J. E Health Medical Commun.","volume":"5 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":"134404810","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
Benefits Measurement of a Plan to Reduce Hypertension in a Healthcare Foundation Using the BCTool 使用BCTool测量医疗基金会降低高血压计划的效益
Int. J. E Health Medical Commun. Pub Date : 2021-11-01 DOI: 10.4018/ijehmc.20211101.oa13
L. Pereira, Vânia Patrício, António Fernandes, José Santos, Ricardo Santos, Carlos M. Jerónimo, Francisco Simões
{"title":"Benefits Measurement of a Plan to Reduce Hypertension in a Healthcare Foundation Using the BCTool","authors":"L. Pereira, Vânia Patrício, António Fernandes, José Santos, Ricardo Santos, Carlos M. Jerónimo, Francisco Simões","doi":"10.4018/ijehmc.20211101.oa13","DOIUrl":"https://doi.org/10.4018/ijehmc.20211101.oa13","url":null,"abstract":"The hypertension is a well know problem and associated with a high salt consuming is one of the commonest chronic diseases.To measure the impact of this consuming it has been applied the methodology provided by the Business Case tool (BC Tool), in a Portuguese foundation for elderly, in order to contribute for Intervention Plan for the reduction of hypertension which aims to reduce salt consumption in the Portuguese population and to improve the control of Hypertension through a phased reduction in salt consumption.This objective has been achieved by changing the availability of foods with lower salt contents and by decreasing the addition of salt in cooking. The results of these measures provided a substantial benefit in terms of Benefits Measurements and Cost Analysis besides the results of SROI measurement in order to obtain the social benefits of this initiative of the Intervention plan to reduce hypertension. Along these results it has been collected the suggestions for improvements that would allow the Sarah Beirão Foundation's response to the needs of its users to be improved","PeriodicalId":375617,"journal":{"name":"Int. J. E Health Medical Commun.","volume":"63 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":"129766429","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
EEG-Based Demarcation of Yogic and Non-Yogic Sleep Patterns Using Power Spectral Analysis 基于脑电图的瑜伽和非瑜伽睡眠模式的功率谱分析
Int. J. E Health Medical Commun. Pub Date : 2021-11-01 DOI: 10.4018/IJEHMC.20211101.OA2
B. Hiremath, N. Sriraam, B. Purnima, S. NithinN., Suresh Babu Venkatasamy, Megha Narayanan
{"title":"EEG-Based Demarcation of Yogic and Non-Yogic Sleep Patterns Using Power Spectral Analysis","authors":"B. Hiremath, N. Sriraam, B. Purnima, S. NithinN., Suresh Babu Venkatasamy, Megha Narayanan","doi":"10.4018/IJEHMC.20211101.OA2","DOIUrl":"https://doi.org/10.4018/IJEHMC.20211101.OA2","url":null,"abstract":"Electroencephalogram (EEG) signals resulting from recordings of polysomnography play a significant role in determining the changes in physiology and behavior during sleep. This study aims at demarcating the sleep patterns of yogic and non-yogic subjects. Frequency domain features based on power spectral density methods were explored in this study. The EEG recordings were segmented into 1s and 0.5s. EEG patterns with four windowing scheme overlaps (0%, 50%, 60%, and 75%) to ensure stationarity of the signal in order to investigate the effect of the pre-processing stage. In order to recognize the yoga and non-yoga group through N3 sleep stage, non-linear KNN classifier was introduced and performance was evaluated in terms of sensitivity and specificity. The experimental results show that modified covariance PSD estimate is the best method in classifying the sleep stage N3 of yogic and non-yogic subjects with 95% confidence interval, sensitivity, specificity, and accuracy of 97.3%, 98%, and 97%, respectively.","PeriodicalId":375617,"journal":{"name":"Int. J. E Health Medical Commun.","volume":"12 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":"116091678","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
Classifier Selection for the Prediction of Dominant Transmission Mode of Coronavirus Within Localities: Predicting COVID-19 Transmission Mode 新型冠状病毒优势传播模式预测的分类器选择:预测新型冠状病毒传播模式
Int. J. E Health Medical Commun. Pub Date : 2021-11-01 DOI: 10.4018/IJEHMC.20211101.oa1
D. Atsa’am, R. Wario
{"title":"Classifier Selection for the Prediction of Dominant Transmission Mode of Coronavirus Within Localities: Predicting COVID-19 Transmission Mode","authors":"D. Atsa’am, R. Wario","doi":"10.4018/IJEHMC.20211101.oa1","DOIUrl":"https://doi.org/10.4018/IJEHMC.20211101.oa1","url":null,"abstract":"The coronavirus disease-2019 (COVID-19) pandemic is an ongoing concern that requires research in all disciplines to tame its spread. Nine classification algorithms were selected for evaluating the most appropriate in predicting the prevalent COVID-19 transmission mode in a geographic area. These include multinomial logistic regression, k-nearest neighbour, support vector machines, linear discriminant analysis, naive Bayes, C5.0, bagged classification and regression trees, random forest, and stochastic gradient boosting. Five COVID-19 datasets were employed for classification. Predictive accuracy was determined using 10-fold cross validation with three repeats. The Friedman's test was conducted, and the outcome showed the performance of each algorithm is significantly different. The stochastic gradient boosting yielded the highest predictive accuracy, 81%. This finding should be valuable to health informaticians, health analysts, and others regarding which machine learning tool to adopt in the efforts to detect dominant transmission mode of the virus within localities. © This article published as an Open Access article distributed under the terms of the Creative Commons Attribution License","PeriodicalId":375617,"journal":{"name":"Int. J. E Health Medical Commun.","volume":"34 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":"123353360","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
Arrhythmia Detection Using Deep Belief Network Extracted Features From ECG Signals 基于深度信念网络提取心电信号特征的心律失常检测
Int. J. E Health Medical Commun. Pub Date : 2021-11-01 DOI: 10.4018/IJEHMC.20211101.OA9
Mahendra Kumar Gourisaria, GM Harshvardhan, Rakshit Agrawal, S. Patra, S. Rautaray, M. Pandey
{"title":"Arrhythmia Detection Using Deep Belief Network Extracted Features From ECG Signals","authors":"Mahendra Kumar Gourisaria, GM Harshvardhan, Rakshit Agrawal, S. Patra, S. Rautaray, M. Pandey","doi":"10.4018/IJEHMC.20211101.OA9","DOIUrl":"https://doi.org/10.4018/IJEHMC.20211101.OA9","url":null,"abstract":"","PeriodicalId":375617,"journal":{"name":"Int. J. E Health Medical Commun.","volume":"17 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":"115607829","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: 8
hQChain: Leveraging Towards Blockchain and Queueing Model for Secure Smart Connected Health hQChain:利用区块链和排队模型实现安全的智能互联健康
Int. J. E Health Medical Commun. Pub Date : 2021-11-01 DOI: 10.4018/IJEHMC.20211101.OA3
Pratyusa Mukherjee, L. Barik, C. Pradhan, S. Patra, Rabindra Kumar Barik
{"title":"hQChain: Leveraging Towards Blockchain and Queueing Model for Secure Smart Connected Health","authors":"Pratyusa Mukherjee, L. Barik, C. Pradhan, S. Patra, Rabindra Kumar Barik","doi":"10.4018/IJEHMC.20211101.OA3","DOIUrl":"https://doi.org/10.4018/IJEHMC.20211101.OA3","url":null,"abstract":"","PeriodicalId":375617,"journal":{"name":"Int. J. E Health Medical Commun.","volume":"362 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":"134229677","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: 6
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