ReviewLa Radiologia medica2020
Artificial intelligence in cardiac radiology.
Review in La Radiologia medica, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 57 papers, 1 of them a synthesis that pooled it.
What it found
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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
57 citing papers in PubMed, 1 synthesis or guideline pooled it, 85 citations in OpenAlex.
- Deep learning in 3D cardiac reconstruction: a systematic review of methodologies and dataset.Medical & biological engineering & computing · 2025Pooled it
- Deep Learning Algorithm-Reconstructed Triple-Rule-Out CT: Image Quality and Performance in Evaluating Coronary Lumen Stenosis.Journal of imaging informatics in medicine · 2026Article
- Deep Learning and Cardiovascular Diseases: An Updated Narrative Review.Journal of clinical medicine · 2026Review
- Clinical application of cardiac computed tomography in cardiomyopathy.The international journal of cardiovascular imaging · 2026Review
- Application of 80 kVp combined with deep learning reconstruction algorithm in overweight patients coronary CT angiography: reduced radiation dose and contrast agent dose.Frontiers in radiology · 2026Article
- Explainable-enhanced AI for diagnosing coronary microvascular dysfunction with multimodal imaging.iScience · 2025Article
- The Role of Machine Learning to Detect Occult Neck Lymph Node Metastases in Early-Stage (T1-T2/N0) Oral Cavity Carcinomas.Head & neck · 2025Article
- Heart-Brain axis: is microvascular dysfunction the link between stroke and Takotsubo syndrome?The international journal of cardiovascular imaging · 2025Review
- Artificial Intelligence in Nuclear Cardiology.Journal of clinical medicine · 2025Review
- Artificial intelligence in coronary artery calcification scoring: Current progress and future directions.Global cardiology science & practice · 2025Review
- Clinical Impact of CT-Based FFR in Everyday Cardiology: Bridging Computation and Decision-Making.Biomedicines · 2025Review
- Artificial Intelligence Performance in Cardiac Magnetic Resonance Strain Analysis for Aortic Stenosis: Validation with Echocardiography and Healthy Controls.Medicina (Kaunas, Lithuania) · 2025Article
- The value of CCTA combined with machine learning for predicting angina pectoris in the anomalous origin of the right coronary artery.Biomedical engineering online · 2024Article
- Review
- Article
- Artificial Intelligence in the Differential Diagnosis of Cardiomyopathy Phenotypes.Diagnostics (Basel, Switzerland) · 2024Review
- Predictive value of CT-based and AI-reconstructed 3D-TAPSE in patients undergoing transcatheter tricuspid valve repair.Frontiers in cardiovascular medicine · 2024Article
- Comparative analysis of left ventricle function and deformation imaging in short and long axis plane in cardiac magnetic resonance imaging.Frontiers in cardiovascular medicine · 2024Article
- Enhanced Myocardial Tissue Visualization: A Comparative Cardiovascular Magnetic Resonance Study of Gradient-Spin Echo-STIR and Conventional STIR Imaging.International journal of biomedical imaging · 2024Article
- Three-Dimensional Measurement of the Uterus on Magnetic Resonance Images: Development and Performance Analysis of an Automated Deep-Learning Tool.Diagnostics (Basel, Switzerland) · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Artificial intelligence (AI) is entering the clinical arena, and in the early stage, its implementation will be focused on the automatization tasks, improving diagnostic accuracy and reducing reading time. Many studies investigate the potential role of AI to support cardiac radiologist in their day-to-day tasks, assisting in segmentation, quantification, and reporting tasks. In addition, AI algorithms can be also utilized to optimize image reconstruction and image quality. Since these algorithms will play an important role in the field of cardiac radiology, it is increasingly important for radiologists to be familiar with the potential applications of AI. The main focus of this article is to provide an overview of cardiac-related AI applications for CT and MRI studies, as well as non-imaging-based applications for reporting and image optimization.
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.