ArticleEuropean heart journal supplements : journal of the European Society of Cardiology2023
Artificial intelligence for advanced analysis of coronary plaque.
Article in European heart journal supplements : journal of the European Society of Cardiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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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.
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Who cites it
7 citing papers in PubMed.
- Advanced quantitative CT for coronary artery disease: integrating stenosis quantification, plaque quantification, and fractional flow reserve-CT.The British journal of radiology · 2026Review
- Lipoprotein(a) and plaque progression: insights from serial coronary computed tomography angiography and quantitative plaque assessment.Frontiers in cardiovascular medicine · 2026Article
- Automatic segmentation of coronary plaques in coronary CT angiography using neural networks.PloS one · 2026Article
- Computed Tomography and Coronary Plaque Analysis.Tomography (Ann Arbor, Mich.) · 2025Review
- Research on artificial intelligence, machine and deep learning in medicine: global characteristics, readiness, and equity.Globalization and health · 2025Article
- Predicting the need for calcium modification techniques using computed tomography coronary angiography.The international journal of cardiovascular imaging · 2025Article
- Predictive value of change in percent calcified plaque burden based on serial coronary computed tomographic angiography for cardiovascular events.Quantitative imaging in medicine and surgery · 2025Article
Corrections and comments
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Authors and funding
4 authors.
Funding
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Abstract
The field of coronary plaque analysis is advancing including more quantitative analysis of coronary artery diseases such as plaque burden, high-risk plaque features, computed tomography-derived fractional flow reserve, and radiomics. Although these biomarkers have shown great promise for the diagnosis and prognosis of cardiac patients in a research setting, many of these advanced analyses are labour and time intensive and therefore hard to implement in daily clinical practice. Artificial intelligence (AI) is playing an increasing role in supporting the quantification of these new biomarkers. AI offers the opportunity to increase efficiency, reduce human error and reader variability and to increase the accuracy of diagnosis and prognosis by automating many processing and supporting clinicians in their decision-making. With the use of AI these novel analysis approaches for coronary artery disease can be made feasible for clinical practice without increasing cost and workload and potentially improve patient care.
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Registered trials
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