Python scikit-fuzzy: developing a fuzzy expert system for diabetes diagnosis

• Published in: IAES International Journal of Artificial Intelligence
• Main Author: Razak T.R.; Ul-Saufie A.Z.; Yusoff M.H.; Ismail M.H.; Fauzi S.S.M.; Zaki N.A.M.
• Format: Article
• Language: English
• Published: Institute of Advanced Engineering and Science 2024
• Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85192955536&doi=10.11591%2fijai.v13.i2.pp1398-1407&partnerID=40&md5=80d93742cb7141044122b13983b26687

Nowadays, improvements in diabetes detection that provide patients with vital information are needed. This is due to the fact that Diabetes mellitus has generated a worldwide epidemic that costs society and people. Also, patients tend to misread symptoms, and clinicians who collect insufficient data may produce erroneous outcomes. Therefore, this study aims to demonstrate that a programme that integrates expert advice such as decisions, recommendations, or solutions is an excellent method for reducing the incidence of diabetes. Specifically, this study intends to implement a fuzzy expert system that can detect and report the early stages of diabetes as a viable approach. Furthermore, since this programme is available to everyone, people may easily self-diagnose themselves if they have a blood glucose monitoring device. However, developing the fuzzy expert system for real-world situations, such as diabetes patients, using any programming tools is not straightforward. Therefore, this study will provide a comprehensive approach to constructing a fuzzy expert system using the popular programming language Python. © 2024, Institute of Advanced Engineering and Science. All rights reserved.