A new review highlights how artificial intelligence is reshaping hypertension management, from wearable monitors to predictive models for cardiovascular, renal, and retinal outcomes. The paper details recent innovations in AI-driven diagnosis, continuous blood pressure monitoring, and risk prediction.

Why It Matters To Your Practice

• Hypertension remains a top contributor to heart, kidney, and brain disease.

• AI-driven tools could streamline diagnosis and personalize patient care.

• Continuous monitoring may improve early intervention and risk assessment.

• Smart algorithms could ease workload and enhance clinical decision-making.

Clinical Implications

• Wearable, cuffless BP monitors use ECG, heart sounds, and impedance data.

• AI algorithms, like Extreme Gradient Boost, predict BP with high accuracy.

• Models forecast hypertension’s impact on multiple organ systems.

• Large language models are emerging for tailored patient management.

Insights

• Validated AI tools offer potential for real-time, remote BP monitoring.

• Personalized risk stratification could target high-risk populations.

• Adoption requires addressing model validation and interpretability issues.

• Ethical, equitable implementation is key for widespread benefit.

The Bottom Line

• AI is poised to transform hypertension care, but requires robust trials and thoughtful integration to realize its promise for improved outcomes.