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HYBRID METHODOLOGY FOR PREDICTING HYPERTENSION IN PATIENTS WITH DYSLIPIDEMIA AND TYPE 2 DIABETES MELLITUS
Keywords:
hypertension, dyslipidemia, multiple logistic regression, type 2 diabetes mellitus, MLFNN, surface plotDOI:
https://doi.org/10.17654/0972361725045Abstract
This study uses statistical computational methods to model hypertension in patients with dyslipidemia and type 2 diabetes. A retrospective analysis of 39 patients from Hospital Universiti Sains Malaysia identified key factors like blood pressure, glucose, and cholesterol. A hybrid model combining bootstrap, logistic regression, and neural networks achieved 99.99% accuracy with a MAD of 0.0001. Eight factors were significantly associated with hypertension, demonstrating the model’s high predictive power and reliability for risk assessment.
Received: March 26, 2025
Accepted: May 8, 2025
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