Machine Learning Driven Insights into Socio-Economic, Demographic, and Health Determinants of Type-II Diabetes: A Tuned Hyperparameter Random Forest Model Using NFHS-5 Data

Random Forest algorithms are extremely effective with early diabetes detection and could help support the design of focused intervention and policy measures.

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Publication Details

Journal
Journal of Pharmacy And Bioallied Sciences
Published
2026-01-22
DOI
https://doi.org/10.4103/jpbs.jpbs_1612_25
Primary Topic
Artificial Intelligence in Healthcare
Type
article
Field-Weighted Citation Impact
0.00
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article

Machine Learning Driven Insights into Socio-Economic, Demographic, and Health Determinants of Type-II Diabetes: A Tuned Hyperparameter Random Forest Model Using NFHS-5 Data

Rajeev Pandey, Hitesh Athwani, Kuhu Awasthi, Meghna Athwani
Journal of Pharmacy And Bioallied Sciences
Artificial Intelligence in Healthcare
article

Machine Learning Driven Insights into Socio-Economic, Demographic, and Health Determinants of Type-II Diabetes: A Tuned Hyperparameter Random Forest Model Using NFHS-5 Data

Rajeev Pandey, Hitesh Athwani, Kuhu Awasthi, Meghna Athwani
article en

Abstract

Random Forest algorithms are extremely effective with early diabetes detection and could help support the design of focused intervention and policy measures.

Journal of Pharmacy And Bioallied SciencesVol. 18(Suppl 1)
University of Lucknow (IN), Sarojini Naidu Medical College (IN), Bennett University (IN)
Openalex Percentile: Top 82%
Artificial Intelligence in Healthcare
DOIOpen Access PDFOpenAlex
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