Correspondence analysis as a screening method for indicants for clinical diagnosis

Abstract
In clinical diagnosis, a patient's symptoms are observed and the probabilities of various diseases are assessed. A widely used method of formalizing this approach is independent Bayes in which symptoms are assumed to be independent conditional on the disease category. Correspondence analysis provides a method for examining the dependence between symptoms and assists in the selection of a reduced set of symptoms for the application of the independent Bayes method. This approach is illustrated on two data sets concerned with patients attending Accident and Emergency departments with chest pain and acute abdominal pain, respectively.