Improvement of an expert system that predict warfarin dosage in turkish patients depending on genetic and non-genetic factors

The importance of genetic engineering has been increasing rapidly in recent years. The vast majority of data about DNA was discovered after 90's. The studies on field gene is increasing day by day and large amounts of data are obtained from these studies that requires analysis. Many studies are done to improve the life quality of mankind by signification of these rapidly increasing stack of data obtained from gene investigations. In this context, extending human life by keeping the drug utilization at optimum level is involved in regarded studies. In this thesis, the concepts of bioinformatics and genom and expert systems are examined. The usage of warfarin is tried to be kept at optimum level by applying data mining algorithms K-nearest neighbor and Bayesian algorithms on the data obtained from Turkish patients.