Proceedings of the MULTINOVA: First International Conference on Artificial Intelligence in Engineering, Healthcare and Sciences (ICAIEHS- 2025)

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Diabetes Risk Analyzer

Authors
Sandali Natekar1, *, Jayshree Bohra1, Kshithij Shetty1, Aditi Shukla1, Trupti Agarkar1
1Dept. of Computer Engineering, Ramrao Adik Institute of Technology, Navi Mumbai, India
*Corresponding author. Email: san.nat.rt21@dypatil.edu
Corresponding Author
Sandali Natekar
Available Online 7 October 2025.
DOI
10.2991/978-94-6463-852-3_16How to use a DOI?
Keywords
Diabetes Prediction; Machine Learning (ML); Type 2 Diabetes; Early Diagnosis; Ensemble Models; Healthcare Analytics; Predictive Modeling
Abstract

Diabetes is classified as a noncommunicable disease with a high-risk profile and includes high prevalence of cardiovascular diseases, kidney failure, or nervous system disorders. As the global prevalence of Type 2 diabetes increases, there is a critical need to identify measures that will remove or reduce the burden that results from the disease. Anticipating the disease allows intervention in a patient’s daily routine and diet and even medications to avoid or postpone the onset of the illness. This paper deals with improving the diagnosis of diabetes using ML approach to construct a probability models that help determine the likelihood of an individual succumbing to diabetes. These models are supplementary to the diagnostic tests currently in use and help provide a more efficient and proactive means of handling diabetes. The study therefore hopes to improve the public health system, lessen the strain on health resources and improve the fight against diabetes as a disease globally.

Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the MULTINOVA: First International Conference on Artificial Intelligence in Engineering, Healthcare and Sciences (ICAIEHS- 2025)
Series
Advances in Intelligent Systems Research
Publication Date
7 October 2025
ISBN
978-94-6463-852-3
ISSN
1951-6851
DOI
10.2991/978-94-6463-852-3_16How to use a DOI?
Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Sandali Natekar
AU  - Jayshree Bohra
AU  - Kshithij Shetty
AU  - Aditi Shukla
AU  - Trupti Agarkar
PY  - 2025
DA  - 2025/10/07
TI  - Diabetes Risk Analyzer
BT  - Proceedings of the MULTINOVA: First International Conference on Artificial Intelligence in Engineering, Healthcare and Sciences (ICAIEHS- 2025)
PB  - Atlantis Press
SP  - 246
EP  - 258
SN  - 1951-6851
UR  - https://doi.org/10.2991/978-94-6463-852-3_16
DO  - 10.2991/978-94-6463-852-3_16
ID  - Natekar2025
ER  -