aceClinical applications of artificial intelligence in hypertension management: current evidence and future perspectives
Hypertension remains the leading modifiable risk factor for cardiovascular morbidity and mortality worldwide, with persistently inadequate blood pressure control despite guideline-directed therapy. The rapid expansion of digital health data and computational capacity has positioned artificial intelligence (AI) as a promising tool for improving hypertension management through enhanced risk prediction, phenotyping, and individualized care. However, important challenges related to external validation, interpretabil…
AI models predicted incident hypertension and cardiovascular risk from EHRs, wearables and multimodal data with AUCs around 0.75 to 0.90, supporting personalized therapy and remote monitoring.
Most AI hypertension studies remain retrospective or internally validated, with few demonstrating external validation or gains in hard outcomes like cardiovascular events or mortality, plus barriers of bias, interpretability, and infrastructure.
Evidence base is largely retrospective and internally validated, with few externally validated studies and scarce large prospective randomized trials showing hard outcomes.
Evidence
- Peer-reviewedHerz2026-07-17
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Truvace Impact Record TRV-2026-0269, v1: “Clinical applications of artificial intelligence in hypertension management: current evidence and future perspectives.” Truvace, 2026-07-19. /record/TRV-2026-0269 (accessed at citation time). sha256 14dd4b02244fd894…
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