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

Title:
Python scikit-fuzzy: developing a fuzzy expert system for diabetes diagnosis
Publisher Information:
Zenodo
Publication Year:
2024
Collection:
Zenodo
Document Type:
Fachzeitschrift article in journal/newspaper
Language:
unknown
ISSN:
2252-8938
Relation:
https://zenodo.org/records/14037527; oai:zenodo.org:14037527
DOI:
10.11591/ijai.v13.i2.pp1398-1407
Rights:
Creative Commons Attribution 4.0 International ; cc-by-4.0 ; https://creativecommons.org/licenses/by/4.0/legalcode
Accession Number:
edsbas.D17DDCE4
Database:
BASE

Weitere Informationen

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 straight forward. Therefore, this study will provide a comprehensive approach to constructing a fuzzy expert system using the popular programming language Python.