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