A Neuro-fuzzy based Medical Intelligent System for the Diagnosis of Hepatitis B
Dalwinder Singh, Sahil Verma, Jimmy Singla
Abstract
Hepatitis B is an infection, which grows the deadly virus in the patients' liver. This severe infection will lead to the various deadly diseases that can infect the liver of an individual completely. Therefore, it is very crucial and become a necessity to detect or identify this Hepatitis B virus at the very first stage or at an introductory stage. by doing so, the life of an individual can be saved for good. Hence, the main purpose of this research effort is to propose an intelligent system that assists in the identification and diagnosis of the Hepatitis B virus in stage 1. This medical diagnostic system is proposed by using the neurofuzzy technique. The input variables or linguistic variables that are used in this study are HBsAg, Anti-HBs or HBsAb, Anti-HBc or HBcAb, HBV DNA and Anti-HBcAg-IgM. Similarly, the output variables of this system are no HBV, acute disease or chronic disease. This hybrid system has been developed by using software named as MATLAB. The diverse parameters that assist in the evaluation of performance are also determined by using the observed values from the proposed system. The accuracy with which the developed medical diagnostic system classifies the result corresponding to the given input is 95.55%.