Abstract
The hepatitis B virus is the most deadly virus, which significantly affects the human liver. The termination of the hepatitis B virus is mandatory and can be done by taking precautions as well as a suitable cure in its introductory stage; otherwise, it will become a severe problem and make a human liver suffer from the most dangerous diseases, such as liver cancer. In this paper, two medical diagnostic systems are developed for the diagnosis of this life-threatening virus. The methodologies used to develop thesemodels are fuzzy logic and the neuro-fuzzy technique. The diverse parameters that assist in the evaluation of performance are also determined by using the observed values from the proposed system for both developedmodels. The classification accuracy of a multilayered fuzzy inference system is 94%. The accuracy with which the developed medical diagnostic system by using Adaptive Network based Fuzzy Interference System (ANFIS) classifies the result corresponding to the given input is 95.55%. The comparison of both developed models on the basis of their performance parameters has been made. It is observed that the neuro-fuzzy technique-based diagnostic system has better accuracy in classifying the infected and non-infected patients as compared to the fuzzy diagnostic system. Furthermore, the performance evaluation concluded that the outcome given by the developed medical diagnostic system by using ANFIS is accurate and correct as compared to the developed fuzzy inference system and also can be used in hospitals for the diagnosis of Hepatitis B disease. In other words, the adaptive neuro-fuzzy inference system has more capability to classify the provided inputs adequately than the fuzzy inference system.