title: Induction of diagnostic test strategies with multi-level information measures.
abstract: This 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.
authors.affiliation: Medical Computing Laboratory, Department of Information Systems and Computer Science, National University of Singapore, Singapore.
authors.forename: C
authors.initials: C
authors.lastname: Cao
authors.forename: T Y
authors.initials: TY
authors.lastname: Leong
authors.forename: P K
authors.initials: PK
authors.lastname: Leong
mesh_terms: D000465:Algorithms; D003663:Decision Trees; D003936:Diagnosis, Computer-Assisted; D006801:Humans