ReviewClinical hypertension2026
Current perspectives and challenges of digital hypertension: artificial intelligence in the management of hypertension.
Review in Clinical hypertension, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
- Explainable Lightweight AI for the Identification of Right-Sided Cardiac Dysfunction in a Saudi Arabian Diabetic Cohort.Journal of clinical medicine · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Hypertension remains a leading global health challenge. However, decades of conventional strategies have failed to achieve adequate blood pressure (BP) control rates. Given the complex pathophysiology and diverse risk factors of hypertension, the primary barriers to its effective management are an inadequate recognition of cardiovascular risk, as well as suboptimal methods for accurate, early-stage diagnosis and phenotyping. This persistent public health problem underscores an urgent need for transformative innovations of hypertension management. Digital hypertension is an emerging field that integrates advanced technologies into the management of hypertension, especially artificial intelligence (AI). Emerging technologies are providing new strategies for hypertension management, including accurate prediction and precision subtyping from large datasets, remote telemedicine support, intelligent BP monitoring, and personalized interventions. This review summarizes recent advancements and challenges in these technologies, particularly AI, offering new insights for realizing precision medicine in the era of digital hypertension.
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.