An Expert System to Diagnose Pneumonia Using Fuzzy Logic

INTRODUCTION: Pneumonia is the most common and widespread killing disease of respiratory system which is difficult to diagnose due to identical clinical signs of respiratory system. AIM: In this research, to diagnose this, a structure of a fuzzy expert system has been offered. This is done in order to help general physicians and the patients make decision and also differentiate among chronic bronchitis, tuberculosis, asthma, embolism, lung cancer. METHODS: This system has been created using fuzzy expert system and it has been created in 4 stages: definition of knowledge system, design of knowledge system, implementation of system, system testing using prototype life cycle methodology. RESULTS: The system has 97 percent sensitivity, 85 percent specificity, 93 percent accuracy to diagnose the disease. CONCLUSION: Framework of the knowledge of specialist physicians using fuzzy model and its rules can help diagnose the disease correctly.