Sequential diagnosis in the independence bayesian framework

Abstract

We present a new approach to test selection in sequential diagnosisf(or classification) in the independence Bayesian framework that resembles thefhypothetico-deductive approach to test selection used by doctors. In spite of itsfrelative simplicity in comparison with previous models of hypotheticodeductivefreasoning, the approach retains the advantage that the relevance of afselected test can be explained in strategic terms. We also examine possiblefapproaches to the problem of deciding when there is sufficient evidence tofdiscontinue testing, and thus avoid the risks and costs associated withfunnecessary tests.