Hybrid methodology for predicting hypertension in patients with dyslipidemia and type 2 diabetes mellitus - Adnan, Mohamad Nasarudin; Wan Ahmad, Wan Muhamad Amir; Mohamad Ghazali, Farah Muna; Aleng, Nor Azlida; Mohd Ibrahim, Mohamad Shafiq; Abdul Halim, Nurfadhlina (Pushpa Publishing House, 2025)
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