Adaptive Neuro-fuzzy Inference System for Hypertension Analysis

Adaptive Neuro-fuzzy inference system (ANFIS) is multi-layer system proposed by Jang, enables to increase the performance by integrates the best features of Artificial Neural Networks and Fuzzy inference system into a single framework. It is a popular framework for solving complex problems. In this present work, an ANFIS is proposed for detection the risk factor of hypertension. In this work, for training the ANFIS system hypertension patient’s data set is collected under the supervision of physician in clinical trials on hypertension patients in civil hospital. Additionally, the performance analysis has been performed using the parameters Specificity and Precision. This paper gives a comprehensive performance analysis of the proposed approach and compares its results with existing Fuzzy Expert System technique. Simulation results have demonstrated that the proposed technique shows a better outcome then existing system in terms of Specificity and Precision. We obtained that the specificity and precision of proposed model results is 93.33% and 98.11% resp. Keywords—Adaptive Neuro-fuzzy Inference System (ANFIS), fuzzy expert system, expert system, hypertension, medical diagnosis.