Intelligent data analysis for medical diagnosis: using machine learning and temporal abstraction

Extensive amounts of knowledge and data stored in medical databases request the development of specialized tools for storing and accessing of data, da ta analysis, and effective use of stored knowledge and data. This paper foc uses on methods and tools for intelligent data analysis, aimed at narrowing the increasing gap between data gathering and data comprehension. The pape r sketches the history of research that led to the development of current i ntelligent data analysis techniques, discusses the need for intelligent dat a analysis in medicine, and proposes a classification of intelligent data a nalysis methods. The main scope of the paper are machine learning and tempo ral abstraction methods and their application in medical diagnosis. A selec tion of methods and diagnostic domains is presented, and the performance an d usefulness of approaches discussed. The paper concludes with the evaluati on of selected intelligent data analysis methods and their applicability in medical diagnosis.