Int. J. E Health Medical Commun.最新文献_第10页

Diagnostic Assessment Techniques and Non-Invasive Biomarkers for Autism Spectrum Disorder 自闭症谱系障碍的诊断评估技术和非侵入性生物标志物

Int. J. E Health Medical Commun. Pub Date : 2019-07-01 DOI: 10.4018/IJEHMC.2019070105

Tanu, D. Kakkar

引用次数: 22

Mobile Health to Support Ageing in Place: A Systematic Review of Reviews and Meta-Analyses 移动医疗就地支持老龄化:综述和荟萃分析的系统综述

Int. J. E Health Medical Commun. Pub Date : 2019-07-01 DOI: 10.4018/IJEHMC.2019070101

N. Rocha, Milton Santos, Margarida Cerqueira, A. Queirós

引用次数: 8

A Cloud-Based Smartphone Solution for Transmitting Bio-Signals From an Emergency Response Vehicle 一种基于云的智能手机解决方案，用于从应急响应车辆传输生物信号

Int. J. E Health Medical Commun. Pub Date : 2019-07-01 DOI: 10.4018/IJEHMC.2019070102

A. Mukhopadhyay, Sidharth Sreekumar, Bobin Xavier, M. Suraj

引用次数: 2

Fuzzy Logic-Based Predictive Model for the Risk of Type 2 Diabetes Mellitus 基于模糊逻辑的2型糖尿病风险预测模型

Int. J. E Health Medical Commun. Pub Date : 2019-07-01 DOI: 10.4018/IJEHMC.2019070104

P. Idowu, Jeremiah Ademola Balogiun

引用次数: 0

An Improved Retinal Blood Vessel Detection System Using an Extreme Learning Machine 一种利用极限学习机改进的视网膜血管检测系统

Int. J. E Health Medical Commun. Pub Date : 2019-07-01 DOI: 10.4018/IJEHMC.2019070103

L. M. D. Sousa, P. Filho, F. Bezerra, A. Neto, Saulo A. F. Oliveira

引用次数: 1

Impact of Privacy Issues on Successful Implementation of Personalized Medicare System: An Empirical Study 隐私问题对个性化医疗保险制度成功实施的影响:实证研究

Int. J. E Health Medical Commun. Pub Date : 2019-07-01 DOI: 10.4018/IJEHMC.2019070106

Sandip Bisui, S. Misra

{"title":"Impact of Privacy Issues on Successful Implementation of Personalized Medicare System: An Empirical Study","authors":"Sandip Bisui, S. Misra","doi":"10.4018/IJEHMC.2019070106","DOIUrl":"https://doi.org/10.4018/IJEHMC.2019070106","url":null,"abstract":"Personalized medicare systems is an emerging field of research, which bears the potential to significantly reduce healthcare expenditures and treatment errors and thereby to revolutionize the entire treatment procedure. In this novel approach, genomic variation in different individuals is duly taken into consideration. However, there exist several serious issues (e.g. privacy concerns) that provide hindrance to large-scale adoption of this medicare system. The main objective of this study has been to identify the privacy issues and to evaluate their impact on successful implementation of this novel medical treatment. The methodology used is empirical and is based on a survey-based post facto procedure. The data collected from the survey are analyzed by using the method of structural modelling analysis. This is an original study in the realm of healthcare management, which reveals that the technology related factors and privacy concerns have considerable impact on the successful implementation of personalized medicare system on a large scale. But the privacy concerns have no significant moderating effect on the impact of technology related factors, so far, the success of implementation of personalized medicine is concerned.","PeriodicalId":375617,"journal":{"name":"Int. J. E Health Medical Commun.","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124948277","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 Analysis of Compression Techniques for Chronic Wound Image Transmission Under Smartphone-Enabled Tele-Wound Network 智能手机远程伤口网络下慢性伤口图像传输压缩技术性能分析

Int. J. E Health Medical Commun. Pub Date : 2019-04-01 DOI: 10.4018/IJEHMC.2019040101

Chinmay Chakraborty

{"title":"Performance Analysis of Compression Techniques for Chronic Wound Image Transmission Under Smartphone-Enabled Tele-Wound Network","authors":"Chinmay Chakraborty","doi":"10.4018/IJEHMC.2019040101","DOIUrl":"https://doi.org/10.4018/IJEHMC.2019040101","url":null,"abstract":"The healing status of chronic wounds is important for monitoring the condition of the wounds. This article designs and discusses the implementation of smartphone-enabled compression technique under a tele-wound network (TWN) system. Nowadays, there is a huge demand for memory and bandwidth savings for clinical data processing. Wound images are captured using a smartphone through a metadata application page. Then, they are compressed and sent to the telemedical hub with a set partitioning in hierarchical tree (SPIHT) compression algorithm. The transmitted image can then be reduced, followed by an improvement in the segmentation accuracy and sensitivity. Better wound healing treatment depends on segmentation and classification accuracy. The proposed framework is evaluated in terms of rates (bits per pixel), compression ratio, peak signal to noise ratio, transmission time, mean square error and diagnostic quality under telemedicine framework. A SPIHT compression technique assisted YDbDr-Fuzzy c-means clustering considerably reduces the execution time (105s), is simple to implement, saves memory (18 KB), improves segmentation accuracy (98.39%), and yields better results than the same without using SPIHT. The results favor the possibility of developing a practical smartphone-enabled telemedicine system and show the potential for being implemented in the field of clinical evaluation and the management of chronic wounds in the future.","PeriodicalId":375617,"journal":{"name":"Int. J. E Health Medical Commun.","volume":"310 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129663044","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: 15

Comparative Performance Analysis of Various Classifiers for Cloud E-Health Users 不同分类器对云电子健康用户的性能比较分析

Int. J. E Health Medical Commun. Pub Date : 2019-04-01 DOI: 10.4018/IJEHMC.2019040105

T. Selvan, B. Balamurugan

{"title":"Comparative Performance Analysis of Various Classifiers for Cloud E-Health Users","authors":"T. Selvan, B. Balamurugan","doi":"10.4018/IJEHMC.2019040105","DOIUrl":"https://doi.org/10.4018/IJEHMC.2019040105","url":null,"abstract":"Several classifiers are prevalent which act as a major drive for almost all supervised machine learning applications. These classifiers, though their objective working looks similar, they vary drastically in their performances. Some of the important factors that cause such variations are the scalability of the dataset, dataset nature, training time estimation, classifying time for the test data, prediction accuracy and the error rate computation. This paper focuses mainly on analyzing the performance of the existing four main classifiers: IF-THEN rule, C4.5 decision trees, naïve Bayes, and SVM classifier. The objective of this research article is to provide the complete statistical performance estimates of the four classifiers to the authenticated cloud users. These users have the access facility in obtaining the essential statistical information about the classifiers in study from the cloud server. Such statistical information might be helpful in choosing the best classifier for their personal or organizational benefits. The classifiers follow the traditional underlying algorithms for classification that is performed in the cloud server. These classifiers are tested on three different datasets namely PIMA, breast-cancer and liver-disorders dataset for performance analysis. The performance analysis indicators used in this research article to summarize the working of the various classifiers are training time, testing time, prediction accuracy and error rate computation. The proposed comparative analysis framework can be used to analyze the performances of the classifiers with respect to any input dataset.","PeriodicalId":375617,"journal":{"name":"Int. J. E Health Medical Commun.","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123872179","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: 3

A Novel Performance Enhancing Task Scheduling Algorithm for Cloud-Based E-Health Environment 基于云的电子健康环境下一种新的性能增强任务调度算法

Int. J. E Health Medical Commun. Pub Date : 2019-04-01 DOI: 10.4018/IJEHMC.2019040106

P. Vijayakumar, P. Pandiaraja, B. Balusamy, Marimuthu Karuppiah

引用次数: 30

Identity Concealment When Uploading Pictures of Patients in a Tele-Medicine System 远程医疗系统上传患者照片时的身份隐藏

Int. J. E Health Medical Commun. Pub Date : 2019-04-01 DOI: 10.4018/IJEHMC.2019040103

J. Azcarraga, John Zachary Raduban, M. C. Gendrano, A. Azcarraga

引用次数: 0