Diagnosis of the diseases: using a GA-fuzzy approach

Authors:
Anish Roychowdhury;Dilip Kumar Pratihar;Nilav Bose;K. P. Sankaranarayanan;N. Sudhahar
Affiliations:
Robotics & AI Lab., Department of Mechanical Engineering, Regional Engineering College, Durgapur 713209, India;Robotics & AI Lab., Department of Mechanical Engineering, Regional Engineering College, Durgapur 713209, India;Robotics & AI Lab., Department of Mechanical Engineering, Regional Engineering College, Durgapur 713209, India;Robotics & AI Lab., Department of Mechanical Engineering, Regional Engineering College, Durgapur 713209, India;Robotics & AI Lab., Department of Mechanical Engineering, Regional Engineering College, Durgapur 713209, India
Venue:
Information Sciences: an International Journal - Special issue: Medical expert systems
Year:
2004

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Abstract

The objective of our study is to design an expert system by modelling the knowledge and thinking process of a doctor. A fuzzy logic controller (FLC) is used to model the process and a genetic algorithm (GA) helps to select a number of good rules from a manually constructed large rule base of an FLC, based on the opinion of 10 doctors. The GA-based tuning is done off-line. Once the optimized rule base of the FLC is obtained, it can diagnose the disease, on-line. The scope of the present work has been extended to two diseases, namely Pneumonia and Jaundice. The symptoms of each disease are fed as inputs to the FLC and the output, i.e., grade of a disease is determined.