Artificial intelligence and machine learning have the potential to transform hypertension care by enhancing blood pressure measurement, risk assessment, and personalized treatment.
AI and machine learning hold transformative potential for hypertension care through improved monitoring and risk prediction, provided challenges regarding validation and bias are addressed.
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.
Karnik et al. (Thu,) conducted a review in Hypertension. Artificial intelligence and machine learning was evaluated. Artificial intelligence and machine learning have the potential to transform hypertension care by enhancing blood pressure measurement, risk assessment, and personalized treatment.