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TitlePreventing patient cardiac arrhythmias by using Data Mining Techniques
Author(s)Portela, Filipe
Santos, Manuel
Silva, Álvaro
Rua, Fernando
Abelha, António
Machado, José Manuel
KeywordsCardiac Arrhythmias
Data Mining
Issue date2014
CitationPortela, F., Filipe Santos, M., Silva, A., Rua, F., Abelha, A., & Machado, J. (2015). Preventing patient cardiac arrhythmias by using data mining techniques. Paper presented at the IECBES 2014, Conference Proceedings - 2014 IEEE Conference on Biomedical Engineering and Sciences: "Miri, Where Engineering in Medicine and Biology and Humanity Meet".
Abstract(s)Cardiac Arrhythmia (CA) is very dangerous and can significantly undermine patient condition. New tools are fundamental to forecast and to prevent possible critical situations. In order to help clinicians acting proactively, predictive data mining real-time models were induced using online-learning. As input variables were considered those acquired at the patient admission and complementary variables (vital signs, laboratory results, therapeutics) hourly collected. The results are very motivating; sensitivity near to 95% was obtained when using Support Vector Machines. The approach explored in this work reveals to be an interesting contribution to the healthcare in terms of predicting CA and a good direction to be further explored.
TypeConference paper
AccessOpen access
Appears in Collections:CAlg - Artigos em livros de atas/Papers in proceedings

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