Smart Health – Potential and Pathways: A Survey

作者: C Arulananthan , Sabibullah Mohamed Hanifa

DOI: 10.1088/1757-899X/225/1/012065

关键词:

摘要: Healthcare is an imperative key field of research, where individuals or groups can be engaged in the self-tracking any kind biological, physical, behavioral, environmental information. In a massive health care data, valuable information hidden. The quantity available unstructured data has been expanding on exponential scale. newly developing Disruptive Technologies handle many challenges that face analysis and ability to extract via analytics. Connected Wellness would retrieve patient's physiological, pathological behavioral parameters through sensors perform inner workings human body analysis. technologies take us from reactive illness-driven proactive wellness-driven system care. It need strive create smart towards instead being illness-driven, today's biggest problem Wellness-driven-analytics application help promote healthiest living environment called "Smart Health", deliver empower based quality living. contributions this survey reveals opens (touches uncovered areas) possible doors line research its computing technologies.

参考文章(19)
J. Archenaa, E.A. Mary Anita, A Survey of Big Data Analytics in Healthcare and Government Procedia Computer Science. ,vol. 50, pp. 408- 413 ,(2015) , 10.1016/J.PROCS.2015.04.021
J. Manyika, Michael Chui, Brad Brown, Jacques Bughin, Richard Dobbs, Charles Roxburgh, Angela Hung Byers, Big data: The next frontier for innovation, competition, and productivity ,(2011)
Hermann Kopetz, Real-Time Operating Systems Springer, Boston, MA. pp. 215- 237 ,(2011) , 10.1007/978-1-4419-8237-7_9
Laurence J. Kotlikoff, Christian Hagist, Health Care Spending: What the Future Will Look Like Research Papers in Economics. ,(2006)
Parisa Rashidi, Alex Mihailidis, A Survey on Ambient-Assisted Living Tools for Older Adults IEEE Journal of Biomedical and Health Informatics. ,vol. 17, pp. 579- 590 ,(2013) , 10.1109/JBHI.2012.2234129
Qinyi Yan, Bo Peng, Gang Su, Bruce E. Cohan, Terry C. Major, Mark E. Meyerhoff, Measurement of tear glucose levels with amperometric glucose biosensor/capillary tube configuration Analytical Chemistry. ,vol. 83, pp. 8341- 8346 ,(2011) , 10.1021/AC201700C
David W. Bates, Suchi Saria, Lucila Ohno-Machado, Anand Shah, Gabriel Escobar, Big Data In Health Care: Using Analytics To Identify And Manage High-Risk And High-Cost Patients Health Affairs. ,vol. 33, pp. 1123- 1131 ,(2014) , 10.1377/HLTHAFF.2014.0041
Daniele Miorandi, Sabrina Sicari, Francesco De Pellegrini, Imrich Chlamtac, Internet of things: Vision, applications and research challenges Ad Hoc Networks. ,vol. 10, pp. 1497- 1516 ,(2012) , 10.1016/J.ADHOC.2012.02.016
Mar Marcos, Jose A. Maldonado, Begoña Martínez-Salvador, Diego Boscá, Montserrat Robles, Interoperability of clinical decision-support systems and electronic health records using archetypes Journal of Biomedical Informatics. ,vol. 46, pp. 676- 689 ,(2013) , 10.1016/J.JBI.2013.05.004
Jimeng Sun, Candace D McNaughton, Ping Zhang, Adam Perer, Aris Gkoulalas-Divanis, Joshua C Denny, Jacqueline Kirby, Thomas Lasko, Alexander Saip, Bradley A Malin, Predicting changes in hypertension control using electronic health records from a chronic disease management program. Journal of the American Medical Informatics Association. ,vol. 21, pp. 337- 344 ,(2014) , 10.1136/AMIAJNL-2013-002033