| Issue |
BIO Web Conf.
Volume 97, 2024
Fifth International Scientific Conference of Alkafeel University (ISCKU 2024)
|
|
|---|---|---|
| Article Number | 00125 | |
| Number of page(s) | 17 | |
| DOI | https://doi.org/10.1051/bioconf/20249700125 | |
| Published online | 05 April 2024 | |
An evaluation framework for diabetes prediction techniques using machine learning
1 University of Kerbala, Kerbala, Iraq
2 University of Kerbala, Kerbala, Iraq
* Corresponding Author: aya.a.hashim@s.uokerbala.edu.iq
Diabetes affects a large segment of society and does not discriminate based on age. Children, young people, or the elderly may be affected by it. By detecting the disease early, clinicians can help patients recover or at least control it. Models based on machine learning algorithms have been proposed by researchers in the field of artificial intelligence to predict disease and determine its type. The purpose of this study was to propose a framework for evaluating studies related to diabetes detection and identification. To develop the proposed model, a systematic review of studies related to the topic was conducted. After proposing and evaluating the framework, 54 relevant studies were evaluated and results inspired by it were drawn.
© The Authors, published by EDP Sciences, 2024
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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