ReviewHypertension (Dallas, Tex. : 1979)2025
Controversy in Hypertension: Pro-Side of the Argument Using Artificial Intelligence for Hypertension Diagnosis and Management.
Review in Hypertension (Dallas, Tex. : 1979), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
11 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Artificial Intelligence in Cardiovascular Medicine: Focus on Hypertension.Hypertension (Dallas, Tex. : 1979) · 2026Pooled it
- Evidence, use cases, and implementation safeguards of large language models in primary care.Communications medicine · 2026Review
- Identifying and mitigating bias in multiple aspects of modern clinical research.Communications medicine · 2026Review
- Personalized artificial intelligence based left ventricular ejection fraction and systolic dysfunction assessment.NPJ digital medicine · 2026Article
- The role of artificial intelligence in hypertension management.Current opinion in nephrology and hypertension · 2026Review
- Do world-wide policy initiatives for regulating health care related artificial intelligence safeguard the declaration of Helsinki?EClinicalMedicine · 2026Review
- Current perspectives and challenges of digital hypertension: artificial intelligence in the management of hypertension.Clinical hypertension · 2026Review
- Access to digital health technologies: personalized framework and global perspectives.Nature reviews. Cardiology · 2026Review
- Artificial intelligence in cardiovascular pharmacotherapy: applications and perspectives.European heart journal · 2025Review
- Machine learning based, subject-specific, gender and race independent, non-invasive estimation of the arterial blood pressure.NPJ cardiovascular health · 2025Article
- Non-genetic factors determine deep learning identified ECG differences between black and white healthy subjects.NPJ cardiovascular health · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
Abstract
Hypertension presents the largest modifiable public health challenge due to its high prevalence, its intimate relationship to cardiovascular diseases, and its complex pathogenesis and pathophysiology. Low awareness of blood pressure elevation and suboptimal hypertension diagnosis serve as the major hurdles in effective hypertension management. Advances in artificial intelligence in hypertension have permitted the integrative analysis of large data sets including omics, clinical (with novel sensor and wearable technologies), health-related, social, behavioral, and environmental sources, and hold transformative potential in achieving large-scale, data-driven approaches toward personalized diagnosis, treatment, and long-term management. However, although the emerging artificial intelligence science may advance the concept of precision hypertension in discovery, drug targeting and development, patient care, and management, its clinical adoption at scale today is lacking. Recognizing that clinical implementation of artificial intelligence-based solutions need evidence generation, this opinion statement examines a clinician-centric perspective of the state-of-art in using artificial intelligence in the management of hypertension and puts forward recommendations toward equitable precision hypertension care.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.