Python scikit-fuzzy: developing a fuzzy expert system for diabetes diagnosis - Rosli Razak, Tajul; Zia Ul-Saufie, Ahmad; Yusoff, Mohamad Hanis; Hafiz Ismail, Mohammad; Mohd Fauzi, Shukor Sanim; Mohd Zaki, Nurul Ain (IAES International Journal of Artificial Intelligence (IJ-AI), 2024)
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.