ReviewLife (Basel, Switzerland)2023
Artificial Intelligence in Cardiovascular CT and MR Imaging.
Review in Life (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 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
26 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Deep learning in 3D cardiac reconstruction: a systematic review of methodologies and dataset.Medical & biological engineering & computing · 2025Pooled it
- Investigation of Concordance between Artificial Intelligence and Manual Measurements of the Cardiac Parameters in Cardiac Magnetic Resonance Imaging.Journal of imaging informatics in medicine · 2026Article
- A narrative review on the use of artificial intelligence in cardiovascular medicine.Cardiovascular diagnosis and therapy · 2026Review
- Assessment of Fractional Flow Reserve from Coronary CT Angiography Using a Deep Learning-Based Algorithm: A Multicenter Retrospective Study.Diagnostics (Basel, Switzerland) · 2026Article
- Artificial Intelligence and Digital Technology in Cardiovascular Imaging: A Narrative Review.Biotech (Basel (Switzerland)) · 2026Review
- Artificial Intelligence in African Cardiovascular Care: Opportunities, Challenges, and Pathways to Improved Outcomes.Public health challenges · 2026Review
- Artificial intelligence-enabled cardiac volumetry for opportunistic screening of cardiomegaly on chest CT: clinical validation with echocardiography.Radiology advances · 2026Article
- Reliability of Gemini 2.5 Pro, ChatGPT 4.1, DeepSeek V3, and Claude Opus 4 in generating standardized CMR protocols.European radiology experimental · 2026Article
- Evaluation of health professionals' perceptions on the use of artificial intelligence in radiology: a questionnaire-based study.BMC medical education · 2025Article
- Applying artificial intelligence to cardiac MRI to diagnose congenital heart disease in low-resource settings such as Sub-Saharan Africa.Communications medicine · 2025Review
- Computed Tomography Advancements in Plaque Analysis: From Histology to Comprehensive Plaque Burden Assessment.Echocardiography (Mount Kisco, N.Y.) · 2025Review
- Chatbots in Radiology: Current Applications, Limitations and Future Directions of ChatGPT in Medical Imaging.Diagnostics (Basel, Switzerland) · 2025Review
- Review
- A Narrative Review of Biomarkers and Imaging in the Diagnosis of Acute Aortic Syndrome.Diagnostics (Basel, Switzerland) · 2025Review
- AI-driven decision making for intravascular device selection in aortic disease. Current insights and prospects.Frontiers in cardiovascular medicine · 2025Review
- Decalcify cardiac CT: unveiling clearer images with deep convolutional neural networks.Frontiers in medicine · 2025Article
- Review
- Review
- Revolutionizing Cardiac Imaging: A Scoping Review of Artificial Intelligence in Echocardiography, CTA, and Cardiac MRI.Journal of imaging · 2024Article
- Imaging biomarkers in cardiac CT: moving beyond simple coronary anatomical assessment.La Radiologia medica · 2024Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The technological development of Artificial Intelligence (AI) has grown rapidly in recent years. The applications of AI to cardiovascular imaging are various and could improve the radiologists' workflow, speeding up acquisition and post-processing time, increasing image quality and diagnostic accuracy. Several studies have already proved AI applications in Coronary Computed Tomography Angiography and Cardiac Magnetic Resonance, including automatic evaluation of calcium score, quantification of coronary stenosis and plaque analysis, or the automatic quantification of heart volumes and myocardial tissue characterization. The aim of this review is to summarize the latest advances in the field of AI applied to cardiovascular CT and MR imaging.
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.