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A novel data-mining approach leveraging social media to monitor and respond to outcomes of diabetes drugs and treatment
KTH, Skolan för teknik och hälsa (STH), Hälso- och systemvetenskap, Systemsäkerhet och organisation.
Department of Biomedical Engineering, University of Houston, Houston, TX, US.
KTH, Skolan för teknik och hälsa (STH), Hälso- och systemvetenskap, Systemsäkerhet och organisation.ORCID-id: 0000-0002-1929-135X
2013 (engelsk)Inngår i: 2013 IEEE Point-of-Care Healthcare Technologies (PHT), New York: IEEE , 2013, s. 264-266Konferansepaper, Publicerat paper (Fagfellevurdert)
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.

sted, utgiver, år, opplag, sider
New York: IEEE , 2013. s. 264-266
Emneord [en]
Data collection, Diabetes mellitus, Medical Devices, Social media, Word lists, Word-clusters
HSV kategori
Identifikatorer
URN: urn:nbn:se:kth:diva-138522DOI: 10.1109/PHT.2013.6461335ISI: 000318858100065Scopus ID: 2-s2.0-84874555555ISBN: 978-146732766-4 (tryckt)OAI: oai:DiVA.org:kth-138522DiVA, id: diva2:681274
Konferanse
1st IEEE-EMBS Conference on Point-of-Care Healthcare Technologies, PHT 2013; Bangalore; India; 16 January 2013 through 18 January 2013
Merknad

QC 20140603

Tilgjengelig fra: 2013-12-19 Laget: 2013-12-19 Sist oppdatert: 2018-01-11bibliografisk kontrollert

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