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Predicting Adverse Drug Events with Confidence
Stockholms universitet, Samhällsvetenskapliga fakulteten, Institutionen för data- och systemvetenskap.
2015 (engelsk)Inngår i: Thirteenth Scandinavian Conference on Artificial Intelligence / [ed] Sławomir Nowaczyk, IOS Press, 2015, 88-97 s.Konferansepaper, Publicerat paper (Fagfellevurdert)
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Text
Abstract [en]

This study introduces the conformal prediction framework to the task of predicting the presence of adverse drug events in electronic health records with an associated measure of statistically valid confidence. The imbalanced nature of the problem was addressed both by evaluating different machine learning algorithms, and by comparing different types of conformal predictors. A novel solution was also evaluated, where different underlying models, each model optimized towards one particular class, were combined into a single conformal predictor. This novel solution proved to be superior to previously existing approaches.

sted, utgiver, år, opplag, sider
IOS Press, 2015. 88-97 s.
Serie
Frontiers in Artificial Intelligence and Applications, ISSN 0922-6389 ; 278
HSV kategori
Forskningsprogram
data- och systemvetenskap
Identifikatorer
URN: urn:nbn:se:su:diva-123964DOI: 10.3233/978-1-61499-589-0-88ISBN: 978-1-61499-588-3 (tryckt)ISBN: 978-1-61499-589-0 (tryckt)OAI: oai:DiVA.org:su-123964DiVA: diva2:878608
Konferanse
Thirteenth Scandinavian Conference on Artificial Intelligence, Halmstad, Sweden, 4-5 November 2015
Tilgjengelig fra: 2015-12-09 Laget: 2015-12-09 Sist oppdatert: 2017-01-16bibliografisk kontrollert

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Totalt: 108 treff
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