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Managing Diabetes Therapy through Datastream Mining
Simon Fong1; Jinan Fiaidhi2; Sabah Mohammed2; Luiz A.M. Moutinho3
2017-10-04
Source PublicationIT PROFESSIONAL
ISSN1520-9202
Volume19Issue:5Pages:50-57
Other Abstract

The authors' datastream mining approach computationally derives real-time decision rules for formulating insulin-dependent diabetes mellitus therapy based on insulin prescription records and patients' blood-glucose reactions.

DOI10.1109/MITP.2017.3680958
URLView the original
Indexed BySCIE
Language英語English
WOS Research AreaComputer Science ; Telecommunications
WOS SubjectComputer Science, Information Systems ; Computer Science, Software Engineering ; Telecommunications
WOS IDWOS:000412595800009
PublisherIEEE COMPUTER SOC
The Source to ArticleWOS
Scopus ID2-s2.0-85031685310
Fulltext Access
Citation statistics
Document TypeJournal article
CollectionDEPARTMENT OF COMPUTER AND INFORMATION SCIENCE
Corresponding AuthorSimon Fong
Affiliation1.University of Macau, Macau SAR
2.Lakehead University, Canada
3.Dublin City University, Ireland
First Author AffilicationUniversity of Macau
Corresponding Author AffilicationUniversity of Macau
Recommended Citation
GB/T 7714
Simon Fong,Jinan Fiaidhi,Sabah Mohammed,et al. Managing Diabetes Therapy through Datastream Mining[J]. IT PROFESSIONAL, 2017, 19(5), 50-57.
APA Simon Fong., Jinan Fiaidhi., Sabah Mohammed., & Luiz A.M. Moutinho (2017). Managing Diabetes Therapy through Datastream Mining. IT PROFESSIONAL, 19(5), 50-57.
MLA Simon Fong,et al."Managing Diabetes Therapy through Datastream Mining".IT PROFESSIONAL 19.5(2017):50-57.
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