Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/99314
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dc.titleInduction of diagnostic test strategies with multi-level information measures.
dc.contributor.authorCao, C.
dc.contributor.authorLeong, T.Y.
dc.contributor.authorLeong, P.K.
dc.date.accessioned2014-10-27T06:02:50Z
dc.date.available2014-10-27T06:02:50Z
dc.date.issued1998
dc.identifier.citationCao, C.,Leong, T.Y.,Leong, P.K. (1998). Induction of diagnostic test strategies with multi-level information measures.. Medinfo. MEDINFO 9 Pt 1 : 477-482. ScholarBank@NUS Repository.
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/99314
dc.description.abstractThis paper presents a method for inducing clinical diagnostic test protocols or strategies from data. We represent testing strategies as a strategy tree. To support induction of strategy tree, we define three information measures: K-level information, K-level information gain, K-level gain ratio, and K-level cost index, for test selection during strategy building. These measures generalize Quinlan's information measures used in decision tree induction. We present theoretical and experimental results to show that the K-level cost index can be used to induce strategy trees in a practical domain.
dc.sourceScopus
dc.typeArticle
dc.contributor.departmentINFORMATION SYSTEMS & COMPUTER SCIENCE
dc.description.sourcetitleMedinfo. MEDINFO
dc.description.volume9 Pt 1
dc.description.page477-482
dc.identifier.isiutNOT_IN_WOS
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