Online approach for Diabetes Diagnosis and Classification with Expert System Modules using Fuzzy Logic

Abstract

Fuzzy Logic is profoundly reasonable and relevant in structuring frameworks in the field of medical; particularly in the various disease diagnosis procedures and in the preparation of treatment strategies. Fuzzy Expert Systems can deal with imprecise, incomplete and uncertain information which comes in the procedure of disease diagnosis and disease treatments. In the proposed work, where a web-based fuzzy expert system modules were designed and developed which will assist to diabetics, diabetologists, practitioners and experts for diabetes diagnosis and its classification. The System’s knowledge base was designed by consulting diabetologists and diabetes patient’s data was collected from the hospital. It is an online rule-based fuzzy expert system, which was designed with the aim to reach people with easy access through the internet. The proposed work exhibits architecture, design, and development of a fuzzy logic based expert system for diabetes disease diagnosis and classification. An open source programming environment and libraries were considered and utilized in the proposed system development.