a fuzzy expert system & neuro-fuzzy system using soft computing for gestational diabetes mellitus diagnosis

gestational diabetes mellitus (gdm) is a kind of diabetes that requires persistent medical care in patient self management education to prevent acute complications. one of the common and main problems in diagnosis of the diabetes is the weakness in its initial stages of the illness. this paper intends to propose an expert system in order to diagnose the risk of gdm by using fis model. the knowledge base was based on the opinion of experts and also by using anfis model in order to extract rules that based on real data. the data were collected from the patient's file in a medical health care center that contains effective risk factors in giving rise to gdm . the effective factors consist of fast blood suger, weight and age in the initial months of pregnancy and the output is the risk of gdm in pregnant women . based on the results , the level of minimum square error in the fuzzy expert system was calculated as 0.227. for diagnosis of illnesses such as diabetes, in lack of accesses to experts ,one can rely on intelligent softwares such as expert systems, wich can assist the speedy and better diagnosis.