As certain diseases are characterized by subjective perceptions of described symptoms, if symptoms are not obvious, physicians can easily mistake them for other illnesses. In order to assist physicians to quickly and accurately diagnose results, a medical diagnostic aid expert system was put forth in this study. The system uses the fuzzy system, back-propagation neural network (BPNN), and fuzzy neural network (FNN) as the core engines of the influenza diagnostic expert system. The three systems were compared whereas the expert system's inferred output served as the data for the prognosis of occurrences of illnesses, thereby providing physicians a diagnostic reference and reducing diagnostic error rates in order to ensure early detections and treatment by doctors and prevent more serious illnesses that may arise due to complications.