Intelligent Platform for Automatic Medical Knowledge Acquisition: Detection and Understanding of Neural Dysfunctions Milan Zorman *, ** , Peter Kokol *, *** , Mitja Leni * , Petra Povalej * , Bruno Stiglic * , Dušan Flisar **** *Laboratory for System Design, Faculty of Electrical Engineering and Computer Science, University of Maribor, Smetanova 17, SI-2000 Maribor, Slovenia **COINS, Complex and Intelligent Systems Institute, Krekova 2, SI-2000 Maribor, Slovenia ***CIMRS, Centre for interdisciplinary and multidisciplinary research and studies, Krekova 2, SI-2000 Maribor, Slovenia ****Maribor Teaching Hospital, Ljubljanska 5, SI-2000 Maribor, Slovenia {milan.zorman, kokol, mitja.lenic, petra.povalej, stiglic}@uni-mb.si dusan.flisar@sb-mb.si Abstract The use of intelligent systems and machine learning methods, capable of automatic decision making based on already solved cases, and data mining, are getting more and more popular. Here we are faced not only with technical problems, but also with limited confidence in machine learning techniques. In some cases methods that may explicitly show the deduction process are not powerful enough. One of the possibilities is to modify/improve the methods so that the users could easily follow the process of decision making. To solve this problem, a few years ago we started to develop a platform, which enables us to develop, test and use different kinds of hybrid methods. These are meant to combine the advantages of the integrated methods – e.g., power and knowledge representation – that contribute to the quality of the acquired knowledge. In this paper we present a way of using the developed platform in order to obtain new knowledge, based on results from neurophysiological measurements We are every pleased with the performance of our intelligent platform. The first results we obtained already show some improvement in comparison to classic machine learning approaches. 1. Introduction The use of intelligent systems and machine learning methods, capable of automatic decision making based on already solved cases, and data mining, are getting more and more popular in fields such as medicine, chemistry and biology. Here we are faced not only with technical Proceedings of the 16th IEEE Symposium on Computer-Based Medical Systems (CBMS’03) 1063-7125/03 $17.00 © 2003 IEEE