ReviewJournal of the American College of Cardiology2019
Artificial Intelligence in Cardiovascular Imaging: JACC State-of-the-Art Review.
Review in Journal of the American College of Cardiology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 325 papers, 6 of them syntheses 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
325 citing papers in PubMed, 6 syntheses or guidelines pooled it.
- The Role of Echocardiography in the Assessment of Epicardial Adipose Tissue: A Systematic Review and Meta-analysis.Current obesity reports · 2026Pooled it
- PRIME 2.0: Proposed Requirements for Cardiovascular Imaging-Related Multimodal-AI Evaluation: An Updated Checklist.JACC. Cardiovascular imaging · 2026Guideline
- Artificial intelligence technology in aortic valve disease: a decade of scientometric and narrative review.Frontiers in cardiovascular medicine · 2026Pooled it
- Application of Machine Learning for Patients With Cardiac Arrest: Systematic Review and Meta-Analysis.Journal of medical Internet research · 2025Pooled it
- The role of artificial intelligence in aortic valve stenosis: a bibliometric analysis.Frontiers in cardiovascular medicine · 2025Pooled it
- Artificial Intelligence in the Heart of Medicine: A Systematic Approach to Transforming Arrhythmia Care with Intelligent Systems.Current cardiology reviews · 2025Pooled it
- Real-time deep learning-based image guiding and automated left ventricular measurements to reduce test-retest variability.Open heart · 2025Trial
- AI-enhanced guidance demonstrated improvement in novices' Apical-4-chamber and Apical-5-chamber views.BMC medical education · 2025Trial
- Atherosclerosis quantification and cardiovascular risk: the ISCHEMIA trial.European heart journal · 2024Trial
- Development of a peripheral blood transcriptomic gene signature to predict bronchopulmonary dysplasia.American journal of physiology. Lung cellular and molecular physiology · 2023Trial
- Machine Learning From Quantitative Coronary Computed Tomography Angiography Predicts Fractional Flow Reserve-Defined Ischemia and Impaired Myocardial Blood Flow.Circulation. Cardiovascular imaging · 2022Trial
- Article
- Myocardial injury in systemic lupus erythematosus and lupus nephritis: a silent threat.Clinical kidney journal · 2026Review
- A deep learning-based algorithm for detecting significant in-stent restenosis in coronary CT angiography.The international journal of cardiovascular imaging · 2026Article
- Intraprocedural echocardiographic guidance in transcatheter mitral valve interventions: from procedure-specific workflows to integrated multimodal platforms.Journal of cardiovascular imaging · 2026Review
- Clinical Applications of Artificial Intelligence in Cardiac CT: From Coronary CT Angiography to CT-Derived Fractional Flow Reserve and Myocardial Perfusion Imaging.Korean journal of radiology · 2026Review
- Comparative validation and clinical utility of an artificial intelligence-based CT-SYNTAX score in complex coronary artery disease.The international journal of cardiovascular imaging · 2026Article
- Artificial Intelligence in Cardiovascular Ultrasound: Clinical Applications, Foundation Models, and the Path to Precision Cardiology.Journal of clinical medicine · 2026Review
- From intravascular imaging to adaptive vascular care: intelligent photonics and digital twins in panvascular disease.Light, science & applications · 2026Review
- The role of artificial intelligence in pediatric cardiovascular imaging: clinical applications and future directions in computed tomography and magnetic resonance imaging.Pediatric radiology · 2026Review
265 more citing papers are in PubMed but not listed here.
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
Abstract
Data science is likely to lead to major changes in cardiovascular imaging. Problems with timing, efficiency, and missed diagnoses occur at all stages of the imaging chain. The application of artificial intelligence (AI) is dependent on robust data; the application of appropriate computational approaches and tools; and validation of its clinical application to image segmentation, automated measurements, and eventually, automated diagnosis. AI may reduce cost and improve value at the stages of image acquisition, interpretation, and decision-making. Moreover, the precision now possible with cardiovascular imaging, combined with "big data" from the electronic health record and pathology, is likely to better characterize disease and personalize therapy. This review summarizes recent promising applications of AI in cardiology and cardiac imaging, which potentially add value to patient 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.