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Artificial Intelligence to Improve Blood Pressure Control: A State-of-the-Art Review

Amogh Karnik, Eugene Yang

2025American Journal of Hypertension12 citationsDOI

Abstract

Hypertension remains a major global health challenge, contributing to significant morbidity and mortality. Advances in artificial intelligence (AI) and machine learning (ML) are transforming hypertension care by enhancing blood pressure (BP) measurement, risk assessment, and personalized treatment. AI-powered technologies have the potential to enable accurate non-invasive BP monitoring and facilitate tailored lifestyle modifications, enhancing adherence and outcomes. ML models can also predict hypertension risk based on demographic, lifestyle, and clinical data, enabling earlier intervention and prevention strategies. However, challenges such as the lack of standardized validation protocols and potential biases in AI systems may widen health disparities. Future research must prioritize rigorous validation across diverse populations and ensure algorithm transparency. By leveraging AI responsibly, we can revolutionize hypertension management, enhance health equity, and improve cardiovascular outcomes.

Topics & Concepts

MedicineBlood pressureCardiologyInternal medicineNon-Invasive Vital Sign MonitoringHeart Rate Variability and Autonomic ControlBlood Pressure and Hypertension Studies
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