Pub Date : 2019-07-01DOI: 10.4018/IJHISI.2019070103
Jooyeon Park, Jinhwa Jang, Insung Ahn
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.
{"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}
Pub Date : 2019-07-01DOI: 10.4018/IJHISI.2019070102
Xiaoli Wang, Kui Su, Lirong Su
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.
{"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}
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.
{"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}
Pub Date : 2019-04-01DOI: 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
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.
{"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}
Pub Date : 2019-04-01DOI: 10.4018/IJHISI.2019040104
Raja Jayaraman, Khaled Saleh, N. King
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.
{"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}
Pub Date : 2019-04-01DOI: 10.4018/IJHISI.2019040102
N. Khumalo, N. Mnjama
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.
{"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}
Pub Date : 2019-04-01DOI: 10.4018/IJHISI.2019040103
Bahae Samhan, K. D. Joshi
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.
{"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}
Pub Date : 2019-01-01DOI: 10.4018/IJHISI.2019010101
Arpita Nagpal, Singh Vijendra
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.
{"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}
Pub Date : 2019-01-01DOI: 10.4018/IJHISI.2019010102
E. Y. Kim, J. Noh, E. Jung, E. Lim
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.
本研究以越南已婚移民妇女为研究对象，探讨心肺复苏术与急救保健训练对其心肺复苏术知识、态度、自我效能感与急救的影响。实验组和对照组在所有因变量上的差异均有统计学意义:心肺复苏知识(t = 3.26, p = 0.002);对心肺复苏的态度(t = 4.46, p = 0.019);自我效能感(t = 2.77, p = 0.010);最后是应对紧急情况的知识(t = 2.77, p = 0.008)。是否参加保健培训在心肺复苏术知识和态度、自我效能感和急救方面存在显著差异，说明保健培训具有教育作用。应不断向越南已婚移民妇女提供心肺复苏术培训和相关信息，以保持这种效果，并帮助向她们提供处理家庭或邻居面临的紧急情况的指导方针。
{"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}
Pub Date : 2018-10-01DOI: 10.4018/IJHISI.2018100102
B. Tiwari, V. Tiwari
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.
{"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}
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