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Stream/Area:
-
Subject:
-
Paper ID:
10.55041/IJSREM22993
Volume:
7 |
6 |
Jun 2023
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
. Diabetes is becoming more common every day, making it important and concerning to predict and diagnose these conditions accurately and efficiently. This research paper focuses on identifying patients who are more likely to have diabetes based on various medical attributes and also examines which attributes are contributing to diabetes. To address this issue, we developed a diabetes prediction system that uses a machine learning algorithm i.e Support Vector Machine (SVM), to predict and classify patients with diabetes. This system helps to relieve a significant amount of pressure on medical professionals by accurately identifying the likelihood of a patient having diabetes. In addition, the diabetes prediction system improves medical care and reduces costs. Overall, this project provides valuable knowledge that can aid in the prediction of diabetes in patients and is implemented in .pynb format.
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Publication Date
5/5/2023
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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No funding information available for this research.
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