The Design And Implementation Of Medical Diagnosis System Based On Fuzzy Reasoning

Nowadays, diagnosis to patients is greatly influenced by doctors’ subjective factors. In this thesis, aiming at this situation, a medical diagnosis system based on fuzzy reasoning technology is proposed. The system is based the actual situation, combining with fuzzy reasoning and auxiliary diagnosis technology. Fuzzy experts system knowledge and common disease pathogenesis and diagnosis methods are applied in the system. The system can imitate biological behavior to reason approximately. The fuzzy inference can be divided into four steps: fuzzification, the rule base, fuzzy reasoning and removing fuzziness. The fuzzification is that the system can transform the patients’ information collected by doctors into a certain membership value through membership function. The rule base refers to that the systematic diagnosis knowledge base is based on doctors’ diagnosis experience, and it can be used as the basis of fuzzy reasoning. The result set follows the fuzzy reasoning which is based on the scope of membership degree. The last step is that diagnosis comes from the calculation of the result set. Through the analysis of experimental results, the fuzzy expert system excludes doctors’ subjective factors in the process of diagnosis, and the doctors can present accurate and objective diagnosis, in the same time, it can reduce the burden of doctors. This system can be used as the means of auxiliary or confirmatory medical diagnosis.