ReviewOpen heart2025
Cardiac CT in the era of artificial intelligence: precision imaging, treatment guidance and optimised risk stratification for coronary artery disease.
Review in Open heart, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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.
- Navigating the intelligence revolution: transforming cardiovascular care through AI-driven innovation.Open heart · 2026Article
- Artificial Intelligence in Cardiovascular Imaging: From Automated Acquisition to Precision Diagnostics and Clinical Decision Support.Medical sciences (Basel, Switzerland) · 2026Review
- Spectral computed tomography characterization of coronary atherosclerotic plaque: principles, imaging biomarkers, and clinical significance.Frontiers in cardiovascular medicine · 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
Coronary artery disease (CAD) remains a leading cause of morbidity and mortality worldwide, and CT imaging plays a crucial role in its diagnosis and management. However, the clinical use of CT is limited by factors, such as suboptimal image quality, diagnostic complexity and the labour-intensive nature of parameter evaluation. Artificial intelligence (AI) is increasingly transforming many areas of medicine. Its integration into CAD CT imaging can enhance image postprocessing, streamline anatomical and functional analyses, support treatment planning and improve risk prediction. This review summarises recent advances in these AI applications, aiming to promote their practical adoption and further development.
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.