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A novel data-mining approach leveraging social media to monitor and respond to outcomes of diabetes drugs and treatment
KTH, School of Technology and Health (STH), Health Systems Engineering, Systems Safety and Management.
Department of Biomedical Engineering, University of Houston, Houston, TX, US.
KTH, School of Technology and Health (STH), Health Systems Engineering, Systems Safety and Management.ORCID iD: 0000-0002-1929-135X
2013 (English)In: 2013 IEEE Point-of-Care Healthcare Technologies (PHT), New York: IEEE , 2013, 264-266 p.Conference paper (Refereed)
Abstract [en]

A novel data-mining method was developed to gauge the experiences of medical devices and drugs by patients with diabetes mellitus. Self-organizing maps were used to analyze forum posts numerically to better understand user opinion of medical devices and drugs. The end-result is a word list compilation that correlates certain positive and negative word cluster groups with medical drugs and devices. The implication of this novel data-mining method could open new avenues of research into rapid data collection, feedback, and analysis that would enable improved outcomes and solutions for public health.

Place, publisher, year, edition, pages
New York: IEEE , 2013. 264-266 p.
Keyword [en]
Data collection, Diabetes mellitus, Medical Devices, Social media, Word lists, Word-clusters
National Category
Information Systems
URN: urn:nbn:se:kth:diva-138522DOI: 10.1109/PHT.2013.6461335ISI: 000318858100065ScopusID: 2-s2.0-84874555555ISBN: 978-146732766-4OAI: diva2:681274
1st IEEE-EMBS Conference on Point-of-Care Healthcare Technologies, PHT 2013; Bangalore; India; 16 January 2013 through 18 January 2013

QC 20140603

Available from: 2013-12-19 Created: 2013-12-19 Last updated: 2014-06-03Bibliographically approved

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