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Int. J. Heal. Inf. Syst. Informatics最新文献

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Comparison of Genetic Variations in Zika Virus Isolated From Different Geographic Regions 不同地理区域分离的寨卡病毒遗传变异的比较
Int. J. Heal. Inf. Syst. Informatics Pub Date : 2019-07-01 DOI: 10.4018/IJHISI.2019070103
Jooyeon Park, Jinhwa Jang, Insung Ahn
{"title":"Comparison of Genetic Variations in Zika Virus Isolated From Different Geographic Regions","authors":"Jooyeon Park, Jinhwa Jang, Insung Ahn","doi":"10.4018/IJHISI.2019070103","DOIUrl":"https://doi.org/10.4018/IJHISI.2019070103","url":null,"abstract":"The Zika virus (ZIKV) belongs to the genus Flavivirus, together with Dengue virus, yellow fever virus, and West Nile virus. The virus, which was first found in Africa in 1947, has spread across the world owing to a lack of effective drugs or vaccines. The complete genome sequence of ZIKV is now available; it includes three structural and seven non-structure genes arranged in the order of capsid, pre-membrane, envelope, NS1, NS2A, NS2B, NS3, NS4A, NS4B, and NS5. Two geographically distinct lineages are known, i.e., Asian and African, but ZIKV exhibits differences in clinical progression among regions.","PeriodicalId":101861,"journal":{"name":"Int. J. Heal. Inf. Syst. Informatics","volume":"5 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":"131023394","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
Research on Improved Apriori Algorithm Based on Data Mining in Electronic Cases 基于电子案例数据挖掘的改进Apriori算法研究
Int. J. Heal. Inf. Syst. Informatics Pub Date : 2019-07-01 DOI: 10.4018/IJHISI.2019070102
Xiaoli Wang, Kui Su, Lirong Su
{"title":"Research on Improved Apriori Algorithm Based on Data Mining in Electronic Cases","authors":"Xiaoli Wang, Kui Su, Lirong Su","doi":"10.4018/IJHISI.2019070102","DOIUrl":"https://doi.org/10.4018/IJHISI.2019070102","url":null,"abstract":"This article makes progress of a commonly used Apriori algorithm, and proposes a new Apriori algorithm based on event ID. In this article, association rules are gained from massive medical data through the new Apriori algorithm. This article proposes and then uses the association rules in the prediction system. This article aims at making the lifestyle-related diseases prediction system provide better service for people, for families and for the whole society. The prediction system can automatically give out health-related information of the user after the person's basic information is put in, and it would also give out some pieces of valuable advice according to the resultant data, helping people realize self-determinant health engagement.","PeriodicalId":101861,"journal":{"name":"Int. J. Heal. Inf. Syst. Informatics","volume":"29 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":"122073281","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
Sentiment Analysis of Twitter Data: A Hybrid Approach Twitter数据的情感分析:一种混合方法
Int. J. Heal. Inf. Syst. Informatics Pub Date : 2019-04-01 DOI: 10.4018/IJHISI.2019040101
Ankit Srivastava, Singh Vijendra, Gurdeep Singh Drall
{"title":"Sentiment Analysis of Twitter Data: A Hybrid Approach","authors":"Ankit Srivastava, Singh Vijendra, Gurdeep Singh Drall","doi":"10.4018/IJHISI.2019040101","DOIUrl":"https://doi.org/10.4018/IJHISI.2019040101","url":null,"abstract":"Over the past few years, the novel appeal and increasing popularity of social networks as a medium for users to express their opinions and views have created an accumulation of a massive amount of data. This evolving mountain of data is commonly termed Big Data. Accordingly, one area in which the application of new techniques in data mining research has significant potential to achieve more precise classification of hidden knowledge in Big Data is sentiment analysis (aka optimal mining). A hybrid approach using Naïve Bayes and Random Forest on mining Twitter datasets is presented here as an extension of previous work. Briefly, relevant data sets are collected from Twitter using Twitter API; then, use of the hybrid methodology is illustrated and evaluated against one with only Naïve Bayes classifier. Results show better accuracy and efficiency in the sentiment classification for the hybrid approach.","PeriodicalId":101861,"journal":{"name":"Int. J. Heal. Inf. Syst. Informatics","volume":"198 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":"127597289","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: 31
A Hybrid Deep Learning and Handcrafted Feature Approach for Cervical Cancer Digital Histology Image Classification 一种混合深度学习和手工特征的宫颈癌数字组织学图像分类方法
Int. J. Heal. Inf. Syst. Informatics Pub Date : 2019-04-01 DOI: 10.4018/IJHISI.2019040105
Haidar A. Almubarak, R. Stanley, Peng Guo, L. Long, Sameer Kiran Antani, G. Thoma, R. Zuna, S. R. Frazier, W. Stoecker
{"title":"A Hybrid Deep Learning and Handcrafted Feature Approach for Cervical Cancer Digital Histology Image Classification","authors":"Haidar A. Almubarak, R. Stanley, Peng Guo, L. Long, Sameer Kiran Antani, G. Thoma, R. Zuna, S. R. Frazier, W. Stoecker","doi":"10.4018/IJHISI.2019040105","DOIUrl":"https://doi.org/10.4018/IJHISI.2019040105","url":null,"abstract":"Cervical cancer is the second most common cancer affecting women worldwide but is curable if diagnosed early. Routinely, expert pathologists visually examine histology slides for assessing cervix tissue abnormalities. A localized, fusion-based, hybrid imaging and deep learning approach is explored to classify squamous epithelium into cervical intraepithelial neoplasia (CIN) grades for a dataset of 83 digitized histology images. Partitioning the epithelium region into 10 vertical segments, 27 handcrafted image features and rectangular patch, sliding window-based convolutional neural network features are computed for each segment. The imaging and deep learning patch features are combined and used as inputs to a secondary classifier for individual segment and whole epithelium classification. The hybrid method achieved a 15.51% and 11.66% improvement over the deep learning and imaging approaches alone, respectively, with a 80.72% whole epithelium CIN classification accuracy, showing the enhanced epithelium CIN classification potential of fusing image and deep learning features.","PeriodicalId":101861,"journal":{"name":"Int. J. Heal. Inf. Syst. Informatics","volume":"381 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":"123302452","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: 28
Improving Opportunities in Healthcare Supply Chain Processes via the Internet of Things and Blockchain Technology 通过物联网和区块链技术改善医疗供应链流程中的机会
Int. J. Heal. Inf. Syst. Informatics Pub Date : 2019-04-01 DOI: 10.4018/IJHISI.2019040104
Raja Jayaraman, Khaled Saleh, N. King
{"title":"Improving Opportunities in Healthcare Supply Chain Processes via the Internet of Things and Blockchain Technology","authors":"Raja Jayaraman, Khaled Saleh, N. King","doi":"10.4018/IJHISI.2019040104","DOIUrl":"https://doi.org/10.4018/IJHISI.2019040104","url":null,"abstract":"Despite key advances in healthcare informatics and management, little progress to address supply chain process-related problems has been made to date. Specifically, key healthcare supply chain processes include product recalls, monitoring of product supply shortages, expiration, and counterfeits. Implementing and executing these processes in a trusted, secure, efficient, globally accessible and traceable manner is challenging due to the fragmented nature of the healthcare supply chain, which is prone to systemic errors and redundant efforts that may compromise patient safety and impact health outcomes adversely. Blockchain, combined with the Internet of things (IoT), is an emerging technology that can offer a practical solution to these challenges. Accordingly, IoT blockchain offers a superior way to track and trace products via a peer-to-peer distributed, secure, and shared ledger of the blockchain network. This article highlights key challenges related to healthcare supply chains, and illustrates how IoT blockchain technologies can play a role in overcoming these challenges now and in the near future.","PeriodicalId":101861,"journal":{"name":"Int. J. Heal. Inf. Syst. Informatics","volume":"9 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":"116878662","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: 52
The Effect of eHealth Information Systems on Health Information Management in Hospitals in Bulawayo, Zimbabwe 电子卫生信息系统对津巴布韦布拉瓦约医院卫生信息管理的影响
Int. J. Heal. Inf. Syst. Informatics Pub Date : 2019-04-01 DOI: 10.4018/IJHISI.2019040102
N. Khumalo, N. Mnjama
{"title":"The Effect of eHealth Information Systems on Health Information Management in Hospitals in Bulawayo, Zimbabwe","authors":"N. Khumalo, N. Mnjama","doi":"10.4018/IJHISI.2019040102","DOIUrl":"https://doi.org/10.4018/IJHISI.2019040102","url":null,"abstract":"EHealth information systems have brought about a lot of positives which include timeous reporting, efficient data analysis, better decision making, coordination and better work processes. Zimbabwe has also adopted the eHealth information systems and this study sought to establish the effects of eHealth information systems on the management of health information in hospitals in Bulawayo, Zimbabwe. The study applies a qualitative research methodology in which a case study research design and a purposive sampling technique were used. Document analysis and face to face interviews were held with a total of eleven research participants.","PeriodicalId":101861,"journal":{"name":"Int. J. Heal. Inf. Syst. Informatics","volume":"19 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":"128069405","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: 4
Disruptive-Technology Avoidance in Healthcare: A Revealed Causal Mapping (RCM) Approach 医疗保健中的破坏性技术避免:揭示的因果映射(RCM)方法
Int. J. Heal. Inf. Syst. Informatics Pub Date : 2019-04-01 DOI: 10.4018/IJHISI.2019040103
Bahae Samhan, K. D. Joshi
{"title":"Disruptive-Technology Avoidance in Healthcare: A Revealed Causal Mapping (RCM) Approach","authors":"Bahae Samhan, K. D. Joshi","doi":"10.4018/IJHISI.2019040103","DOIUrl":"https://doi.org/10.4018/IJHISI.2019040103","url":null,"abstract":"Disruptive innovation has transformed business activities as well as individuals throughout a variety of industries. In healthcare, the implementation of electronic health records (EHR) innovation has changed the way healthcare organizations handle patient records. Despite the potential benefits EHR can bring to healthcare organizations, there is evidence to show that healthcare providers are avoiding EHR innovations. Little research in information system mainstream research has addressed this phenomenon. To understand EHR avoidance, a mid-range theory is evoked from this textual analysis of responses gathered from healthcare providers at a large international hospital. The data was analyzed by applying a revealed causal mapping technique (RCM). Results of the study revealed not only the key constructs surrounding EHR avoidance, but also the underlying concepts that are shaping each of these constructs. This study demonstrated that the use of the RCM methodology yielded concepts and constructs of EHR avoidance that are not suggested by generalized theory, and revealed main interactions and linkages between these constructs.","PeriodicalId":101861,"journal":{"name":"Int. J. Heal. Inf. Syst. Informatics","volume":"14 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":"130590481","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
Coupling Multivariate Adaptive Regression Spline (MARS) and Random Forest (RF): A Hybrid Feature Selection Method in Action 多变量自适应样条回归(MARS)和随机森林(RF)耦合:一种实际的混合特征选择方法
Int. J. Heal. Inf. Syst. Informatics Pub Date : 2019-01-01 DOI: 10.4018/IJHISI.2019010101
Arpita Nagpal, Singh Vijendra
{"title":"Coupling Multivariate Adaptive Regression Spline (MARS) and Random Forest (RF): A Hybrid Feature Selection Method in Action","authors":"Arpita Nagpal, Singh Vijendra","doi":"10.4018/IJHISI.2019010101","DOIUrl":"https://doi.org/10.4018/IJHISI.2019010101","url":null,"abstract":"In this article, a new algorithm to select the relevant features is proposed for handling microarray data with the specific aim of increasing classification accuracy. In particular, the optimal genes are extracted using filter and wrapper feature selection algorithms. Here, the use of non-parametric regression algorithm called Multivariate Adaptive Regression Spline (MARS) followed by proposed Random Forest Statistical Test (RFST) algorithm are being studied. The study evaluates the comparative performance of the results of RFST and MARS with existing algorithms on ten standard microarray datasets. For performance analysis, three parameters are taken into consideration, namely, the number of selected features, runtime, and classification accuracy. Experimental results indicate that different feature selection algorithms yield different candidate gene subset; therefore, a Hybrid approach is applied to determine the best candidate genes to provide maximum information about the disease. The findings foretell that the RFST is performing better on six out of ten datasets whereas MARS is performing better on other datasets.","PeriodicalId":101861,"journal":{"name":"Int. J. Heal. Inf. Syst. Informatics","volume":"1995 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121070526","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
Development and Application of an Infant and Toddler Healthcare Program for Marriage-Migrant Women 已婚移民妇女婴幼儿保健方案的制定与应用
Int. J. Heal. Inf. Syst. Informatics Pub Date : 2019-01-01 DOI: 10.4018/IJHISI.2019010102
E. Y. Kim, J. Noh, E. Jung, E. Lim
{"title":"Development and Application of an Infant and Toddler Healthcare Program for Marriage-Migrant Women","authors":"E. Y. Kim, J. Noh, E. Jung, E. Lim","doi":"10.4018/IJHISI.2019010102","DOIUrl":"https://doi.org/10.4018/IJHISI.2019010102","url":null,"abstract":"This study was conducted among Vietnamese marriage-migrant women to investigate the effect of both cardiopulmonary resuscitation (CPR) and first aid healthcare trainings on their knowledge and attitude towards CPR, self-efficacy, and first-aid. The experimental and control groups revealed statistically significant differences across all dependent variables: knowledge of CPR (t = 3.26, p = 0.002); attitude towards CPR (t = 4.46, p = 0.019); self-efficacy during CPR (t = 2.77, p = 0.010); and finally, knowledge on coping with emergency situations (t = 2.77, p = 0.008). A significant difference was indicated in their knowledge and attitude towards CPR, self-efficacy, and first aid depending on whether they attended the healthcare training program, which suggested its educative effect. CPR training and relevant information should be continually provided to Vietnamese marriage-migrant women to maintain this effect, and help provide them with guidelines to deal with an emergency situation faced by their family or neighbors.","PeriodicalId":101861,"journal":{"name":"Int. J. Heal. Inf. Syst. Informatics","volume":"79 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122937115","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
An Intelligent Multi-Objective Framework of Pervasive Information Computing 普适信息计算智能多目标框架
Int. J. Heal. Inf. Syst. Informatics Pub Date : 2018-10-01 DOI: 10.4018/IJHISI.2018100102
B. Tiwari, V. Tiwari
{"title":"An Intelligent Multi-Objective Framework of Pervasive Information Computing","authors":"B. Tiwari, V. Tiwari","doi":"10.4018/IJHISI.2018100102","DOIUrl":"https://doi.org/10.4018/IJHISI.2018100102","url":null,"abstract":"This article describes how electronic healthcare has been the key application of pervasive computing innovations to enhance healthcare quality and protect human lives. Specific patients of constant sicknesses and elderly individuals, by and large, may oblige continuous observing of their wellbeing status wherever they are. In this regard, remote patient monitoring technology plays the various important role through wearable devices to monitor patient's physiological figures. But, this must ensure some broad issues like, wearability, adaptability, interoperability, integration, security, and network efficiency. This article proposes a data-driven multi-layer architecture for pervasively remote patient monitoring that incorporates aforesaid issues. It enables the patient's care at the real time and supports anywhere and anytime requirement with using network infrastructure efficiently.","PeriodicalId":101861,"journal":{"name":"Int. J. Heal. Inf. Syst. Informatics","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125016258","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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