Data Mining and Knowledge Discovery Handbook, 2 Edition part 114. Knowledge Discovery demonstrates intelligent computing at its best, and is the most desirable and interesting end-product of Information Technology. To be able to discover and to extract knowledge from data is a task that many researchers and practitioners are endeavoring to accomplish. There is a lot of hidden knowledge waiting to be discovered – this is the challenge created by today’s abundance of data. Data Mining and Knowledge Discovery Handbook, 2nd Edition organizes the most current concepts, theories, standards, methodologies, trends, challenges and applications of data mining (DM) and knowledge discovery. | 58 Data Mining in Medicine Nada Lavrac1 and Blaz Zupan2 1 JoZef Stefan Institute Jamova 39 1000 Ljubljana Slovenia Nova Gorica Polytechnic Vipavska 13 5000 Nova Gorica Slovenia 2 Faculty of Computer and Information Science University of Ljubljana TrZaska 25 1000 Ljubljana Slovenia Department of Molecular and Human Genetics Baylor College of Medicine 1 Baylor Plaza Houston TX 77030 USA Summary. Extensive amounts of data stored in medical databases require the development of specialized tools for accessing the data data analysis knowledge discovery and effective use of stored knowledge and data. This chapter focuses on Data Mining methods and tools for knowledge discovery. The chapter sketches the selected Data Mining techniques and illustrates their applicability to medical diagnostic and prognostic problems. Key words Data Mining in Medicine Inductive Logic Programming Decision Trees Rule Induction Case-based Reasoning Instance-based Learning Supervised Learning Neural Networks Introduction Extensive amounts of knowledge and data stored in medical databases require the development of specialized tools for accessing the data data analysis knowledge discovery and effective use of stored knowledge and data since the increase in data volume causes difficulties in extracting useful information for decision support. The traditional manual data analysis has become insufficient and methods for efficient computer-based analysis indispensable such as the technologies developed in the area of Data Mining and knowledge discovery in databases Frawley 1991 . Knowledge discovery in databases is frequently defined as a process Fayyad 1996 consisting of the following steps understanding the domain forming the data set and cleaning the data extracting of regularities hidden in the data thus formulating knowledge in the form of patterns or models this step is referred to as Data Mining DM postprocessing of discovered knowledge and exploiting the results. Important issues that .
