Hybrid systems for medical data analysis and decision making-a case study on varicose vein disorders

Abstract

This paper examines the applicability of intelligent information processing techniques for the analysis of vascular laboratory data associated with varicose vein disorders. In the first section a brief description of varicose disease is provided. Next, the notion of applying different types of neural network to learning the dynamics of the disease is examined in two experiments. Subsequent to these, a new approach to visualising the output of a Kohonen network is presented. A brief discussion then follows on an architecture for combining these networks into an intelligent hybrid decision making system. Finally, directions for future research are discussed.