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An innovative platform for person-centric health and wellness support

Citation

Banos, O and Amin, MB and Khan, WA and Afzel, M and Ahmad, M and Ali, M and Ali, T and Ali, R and Bilal, M and Han, M and Hussain, J and Hussain, M and Hussain, S and Hur, TH and Bang, JH and Hyunh-The, T and Idris, M and Kang, DW and Park, SB and Siddiqui, H and Vui, LB and Fahim, M and Khattak, AM and Kang, BH and Lee, S, An innovative platform for person-centric health and wellness support, Bioinformatics and Biomedical Engineering Third International Conference (IWBBIO 2015) Proceedings, Part II, 15-17 April 2015, Granada, Spain, pp. 131-140. ISBN 9783319164793 (2015) [Refereed Conference Paper]


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Copyright Statement

Copyright 2015 Springer International Publishing

Official URL: http://dblp2.uni-trier.de/db/journals/lncs.html

DOI: doi:10.1007/978-3-319-16480-9_14

Abstract

Modern digital technologies are paving the path to a revolutionary new concept of health and wellness care. Nowadays, many new solutions are being released and put at the reach of most consumers for promoting their health and wellness self-management. However, most of these applications are of very limited use, arguable accuracy and scarce interoperability with other similar systems. Accordingly, frameworks that may orchestrate, and intelligently leverage, all the data, information and knowledge generated through these systems are particularly required. This work introduces Mining Minds, an innovative framework that builds on some of the most prominent modern digital technologies, such as Big Data, Cloud Computing, and Internet of Things, to enable the provision of personalized healthcare and wellness support. This paper aims at describing the efficient and rational combination and interoperation of these technologies, as well as their integration with current and future personalized health and wellness services and business.

Item Details

Item Type:Refereed Conference Paper
Keywords:human behavior, context-awareness, big data, big information, big knowledge, cloud computing, quanti ed self, digital health, health devices, social networks, user interface, user experience, knowledge bases, personalized recommendations
Research Division:Information and Computing Sciences
Research Group:Data Format
Research Field:Data Format not elsewhere classified
Objective Division:Information and Communication Services
Objective Group:Information Services
Objective Field:Information Services not elsewhere classified
Author:Kang, BH (Professor Byeong Kang)
ID Code:107242
Year Published:2015
Deposited By:Computing and Information Systems
Deposited On:2016-03-08
Last Modified:2017-11-20
Downloads:0

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