Design of Framework to Reduce the Risk of Diabetic using Machine Learning

Design of Framework to Reduce the Risk of Diabetic using Machine Learning

Saroj Kumar Gupta

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Dr. Md. Vaseem Naiyer

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Design of Framework to Reduce the Risk of Diabetic using Machine Learning

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Abstract

Diabetes is a serious disease that spreads rapidly around the world and is first surprising. Its danger factors are therefore quite high. A different technique to identify diabetes at an early stage is to gradually decline in general health. This approach will reveal the health of the body’s organs before symptoms manifest. Using machine learning approaches, a framework for the diabetes prediction system is built in this research paper’s first stages. One popular method for streamlining the diabetes screening process is machine learning. A developed system using a machine learning algorithm and the PIMA health dataset. Using a health analyzer machine, health checks are performed. Diabetic and non-diabetic individuals are separated using the Support Vector machine (SVM) approach. The outcome displays the PIMA accuracy of the SVM algorithm.

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Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

How to Cite This Article

Saroj Kumar Gupta. 2026. \u201cDesign of Framework to Reduce the Risk of Diabetic using Machine Learning\u201d. Global Journal of Research in Engineering - J: General Engineering GJRE-J Volume 22 (GJRE Volume 22 Issue J4): .

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GJRE Volume 22 Issue J4
Pg. 39- 46

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Journal Specifications

Crossref Journal DOI 10.17406/gjre

Print ISSN 0975-5861

e-ISSN 2249-4596

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GJRE-J Classification: DDC Code: 006.312 LCC Code: QA76.9.D343

Submission ReceivedNovember 18, 2022
Peer Review Double Blind
Handling Editor
Accepted November 25, 2022
Published December 30, 2022

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v1.2

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January 20, 2023

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