Degree Name

Master of Engineering (Hons.)


Department of Electrical and Computer Engineering


Most of the biomedical tests in pathology produce quantitative results. The test results are interpreted by an expert to diagnose a medical condition. The interpretation of raw data, particularly when the high number of patients is considered, is quite repetitive and labour intensive. A decision support system has been under study in this work to interpret the raw pathology data and produce more advanced information on the condition of the patient and the nature of the disease while reducing the frequency of misjudgment due to fatigue. The developed system simulates human judgment and decision making in such process using the Fuzzy Logic Control approach. The work is focused on microurine test data. In the course of the thesis the employed method is introduced and the design of the decision support system is described. The performance of the system is validated by comparing its results against the expert's opinion for three sets of opportunistically collected pathology data sets.