IAES International Journal of Artificial Intelligence (IJ-AI)
Vol 13, No 2: June 2024

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

Rosli Razak, Tajul (Unknown)
Zia Ul-Saufie, Ahmad (Unknown)
Yusoff, Mohamad Hanis (Unknown)
Hafiz Ismail, Mohammad (Unknown)
Mohd Fauzi, Shukor Sanim (Unknown)
Mohd Zaki, Nurul Ain (Unknown)



Article Info

Publish Date
01 Jun 2024

Abstract

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.

Copyrights © 2024






Journal Info

Abbrev

IJAI

Publisher

Subject

Computer Science & IT Engineering

Description

IAES International Journal of Artificial Intelligence (IJ-AI) publishes articles in the field of artificial intelligence (AI). The scope covers all artificial intelligence area and its application in the following topics: neural networks; fuzzy logic; simulated biological evolution algorithms (like ...