Discovering medical knowledge with genetic algorithm

This paper reviews our work in the area of knowledge discovery in databases . We have developed a genetic algorithm based machine learning system which was successfully applied to discover diagnostic knowledge from female urin ary incontinence and vertigo data. Comparisons with other methods suggest t hat genetic algorithms are a competitive method to discover knowledge. We a lso discuss an expert system for the differential diagnosis of female urina ry incontinence that utilises the discovered knowledge. In addition, recent research of data pre-processing with outlier identification and removal is presented.