Mediative neuro fuzzy inference and mediative fuzzy expert system for the identification of severity diagnosis of the dengue patients

This research paper presents a new approach to the diagnosis of dengue patients based on a new Mediative neuro-fuzzy method for Sugeno’s inference system. We design a Mediative Neuro-Fuzzy System (MNFS) to adapt the antecedent and consequent part of the inference fuzzy system. We also used a fuzzy optimization technique to optimize the coefficients of the functions which represents the consequent part used for Sugeno’s inference system. This article represents a combined study between Sugeno’s fuzzy expert system and Mediative based neuro-fuzzy system with fuzzy optimization technique for the diagnosis of dengue in the patients. We have also introduced a new concept for the formulation of membership/non-membership function of the input data on the basis of the trend of data by curve fitting. We applied our method on the input data set which has been collected from Lala Lajpat Rai Memorial Medical College (LLRMC) located in Meerut, Uttar Pradesh, India. These input factors include Temperature, Sugar, Pulse rate (PR), Age, Weight, Cough, Laboratory reports of Dengue, Chills, Headache, Blood Pressure (BP), Muscle pain and Chest pain. The output factors have also been classified into three attributes with the condition of the patients. We also include some numeric computation at the end of the research paper. The main objective of this research paper is to develop a mathematical model for the diagnosis of dengue patients based on Neural Network (NN) models.