Predicting high blood pressure using machine learning models in low- and middle-income countries.

Responding to the rising global prevalence of noncommunicable diseases (NCDs) requires improvements in the management of high blood pressure. Therefore, this study aims to develop an explainable machine learning model for predicting high blood pressure, a key NCD risk factor, using data from the STEPwise approach to NCD risk factor surveillance (STEPS) surveys. Nationally representative samples of adults aged 18-69 years were acquired from 57 countries spanning six World Health Organization (WHO) regions.