Multiperspective recognition applied to the computer-aided medical diagnosis - A comparative study of methods

This paper deals with the multiperspective recognition technique applied to the computer-aided decisions in medicine. For three different concepts of multi perspective classification, i.e. direct, decomposed independent and decomposed dependent approach, several decision algorithms are presented. They are: probabilistic (empirical Bayes) algorithm, nearest neighbour algorithm, fuzzy method and artificial neural network of the back propagation and counter propagation types. Proposed methods and algorithms have been applied to the computer-aided diagnosis of chronic renal failure and decisions in non-Hodgkin lymphoma. Results of experimental investigations on the real data and outcomes of the comparative analysis of discussed algorithms are presented.