ReviewAmerican heart journal plus : cardiology research and practice2025
Artificial intelligence enhanced contemporary pulmonary hypertension care.
Review in American heart journal plus : cardiology research and practice, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 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
3 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Artificial Intelligence in Cardiovascular Medicine: Focus on Hypertension.Hypertension (Dallas, Tex. : 1979) · 2026Pooled it
- Comment on "Artificial intelligence enhanced contemporary pulmonary hypertension care".American heart journal plus : cardiology research and practice · 2026Article
- Artificial intelligence in echocardiography: a position statement from the British Society of Echocardiography.Echo research and practice · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
All-cause pulmonary hypertension (PH) is associated with increased mortality and an enormous public health concern. However, given its complexity, multiple potential etiologies and inherent diagnostic challenges, PH diagnosis may be delayed or missed entirely. Artificial Intelligence (AI) shows potential to provide a simple but multifaceted, personalized approach for early identification of PH. AI-assisted patient triage may help highlight individuals requiring further investigation. Echocardiography may improve the identification of PH due to left heart disease and PH from other causes using a combination of AI systems such as image guidance, auto-measurement, deep phenotyping and smart reporting. Multi-level AI integrating clinical and echocardiographic data has the potential to democratize access to medical care and assist in selecting those most at risk for thorough evaluation at expert centers. In this state-of-the-art review, we discuss how new technology including AI can assist in improving the diagnosis and management of PH.
Indexed as
Identifiers
What Socratic 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 Socratic graph.