ReviewCurrent cardiology reports2022
Current State and Future Perspectives of Artificial Intelligence for Automated Coronary Angiography Imaging Analysis in Patients with Ischemic Heart Disease.
Review in Current cardiology reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 1 of them a synthesis that pooled it.
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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
19 citing papers in PubMed, 1 synthesis or guideline pooled it, 31 citations in OpenAlex.
- Artificial Intelligence in the Heart of Medicine: A Systematic Approach to Transforming Arrhythmia Care with Intelligent Systems.Current cardiology reviews · 2025Pooled it
- A novel hybrid segmentation method coupled with deep learning for coronary artery extraction from coronary CT angiography.The international journal of cardiovascular imaging · 2026Article
- Deep Learning and Cardiovascular Diseases: An Updated Narrative Review.Journal of clinical medicine · 2026Review
- Predicting cardiac index from coronary angiogram videos: a novel application of 3D convolutional neural networks.BMJ digital health & AI · 2026Article
- Bioresorbable Scaffolds for Coronary Revascularization: From Concept to Clinical Maturity.Journal of cardiovascular development and disease · 2025Review
- Applications of Artificial Intelligence in Chronic Total Occlusion Revascularization: From Present to Future-A Narrative Review.Medicina (Kaunas, Lithuania) · 2025Review
- Deep Learning-Based Segmentation of Coronary Arteries and Stenosis Detection in X-Ray Coronary Angiography.JACC. Advances · 2025Article
- Harnessing Artificial Intelligence in Interventional Cardiology: A Systematic Review of Current Applications.Cureus · 2025Review
- Linking sequence restoration capability of shuffled coronary angiography to coronary artery disease diagnosis.Scientific reports · 2025Article
- Artificial Intelligence in Coronary Artery Interventions: Preprocedural Planning and Procedural Assistance.Journal of the Society for Cardiovascular Angiography & Interventions · 2025Review
- Validation of machine learning-based risk stratification scores for patients with acute coronary syndrome treated with percutaneous coronary intervention.European heart journal. Digital health · 2024Article
- Artificial intelligence-assisted measurements of coronary computed tomography angiography parameters such as stenosis, flow reserve, and fat attenuation for predicting major adverse cardiac events in patients with coronary arterial disease.Biomolecules & biomedicine · 2024Article
- Review
- Review
- Optimizing ensemble U-Net architectures for robust coronary vessel segmentation in angiographic images.Scientific reports · 2024Article
- Explainable machine learning using echocardiography to improve risk prediction in patients with chronic coronary syndrome.European heart journal. Digital health · 2024Article
- A cardiologist's guide to machine learning in cardiovascular disease prognosis prediction.Basic research in cardiology · 2023Review
- Editorial: Digital Solutions in Cardiology.Frontiers in cardiovascular medicine · 2022Article
- Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors at 4 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purpose of reviewArtificial intelligence (AI) applications in (interventional) cardiology continue to emerge. This review summarizes the current state and future perspectives of AI for automated imaging analysis in invasive coronary angiography (ICA). RECENT
findingsRecently, 12 studies on AI for automated imaging analysis In ICA have been published. In these studies, machine learning (ML) models have been developed for frame selection, segmentation, lesion assessment, and functional assessment of coronary flow. These ML models have been developed on monocenter datasets (in range 31-14,509 patients) and showed moderate to good performance. However, only three ML models were externally validated. Given the current pace of AI developments for the analysis of ICA, less-invasive, objective, and automated diagnosis of CAD can be expected in the near future. Further research on this technology in the catheterization laboratory may assist and improve treatment allocation, risk stratification, and cath lab logistics by integrating ICA analysis with other clinical characteristics.
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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.