Digital Precision Hypertension: AI-Driven Monitoring, Personalized Treatment and Real-World Implementation

Hypertension leftovers a leading global health challenge, causal to increased cardiovascular morbidity and mortality despite advances in pharmacotherapy and lifestyle interventions. Traditional hypertension management often follows a one-size-fits-all approach, failing to account for the heterogeneity of patient physiology, genetics, and environmental factors. The emergence of digital precision medicine, empowered by artificial intelligence [AI], is transforming this paradigm by enabling data-driven, patient-specific hypertension care. AI-integrated wearable sensors, mobile health applications, and remote monitoring platforms now facilitate continuous, real-time blood pressure tracking and behavioural analysis. These technologies generate large-scale datasets that can identify hidden patterns, predict risk trajectories, and personalise therapeutic interventions. Machine learning algorithms, when combined with clinical, genomic, and lifestyle data, enhance diagnostic accuracy and treatment optimisation—supporting decisions on drug selection, dosage titration, and lifestyle modification strategies tailored to individual needs. Furthermore, the integration of digital twins and cloud-based analytics provides a comprehensive representation of cardiovascular dynamics, fostering proactive and preventive care models. However, real-world implementation faces challenges including data privacy, interoperability, algorithmic bias, and regulatory compliance. Bridging these gaps requires collaboration among clinicians, data scientists, policymakers, and technology developers to ensure equity and clinical validity. This review explores the intersection of AI, digital monitoring, and precision therapeutics in hypertension management, critically evaluating current advancements, translational hurdles, and emerging opportunities. By merging precision medicine principles with intelligent digital systems, the future of hypertension care is envisioned as predictive, preventive, personalised, and participatory (P4 medicine)—enhancing both clinical outcomes and patient empowerment.