Machine Learning and Artificial Intelligence for Research on Hypertension

Am J Hypertens. 2025 Apr 19:hpaf051. doi: 10.1093/ajh/hpaf051. Online ahead of print.

Abstract

Hypertension continues to be the leading modifiable risk factor for mortality globally, contributing significantly to cardiovascular disease. According to the World Health Organization, hypertension affects an estimated 1.28 billion adults globally, yet nearly half of these individuals are unaware of their condition, and many remain untreated or inadequately managed1. The American Heart Association (AHA) 2017 Hypertension Guidelines define hypertension as blood pressure (BP) ≥130/80 mmHg and recommend a target BP of <130-140/80 mmHg for most adults. Effective management of hypertension is crucial in reducing morbidity and mortality, and current clinical guidelines emphasize the importance of early detection, lifestyle modifications, and pharmacological treatment to mitigate long-term health risks. With the recent development and advancement of artificial intelligence (AI) and machine learning (ML), the landscape for hypertension care and research is evolving at an accelerating pace to improve health outcomes worldwide.