在一个多样化的真实世界队列中，对一种用于冠状动脉CT血管造影（CCTA）动脉粥样硬化斑块和狭窄定量分析的全自动化深度学习解决方案进行验证。 - Suppr | 超能文献

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本文引用的文献

1

Deep learning-enabled coronary CT angiography for plaque and stenosis quantification and cardiac risk prediction: an international multicentre study.深度学习辅助冠状动脉 CT 血管造影术进行斑块和狭窄定量及心脏风险预测：一项国际多中心研究。

Lancet Digit Health. 2022 Apr;4(4):e256-e265. doi: 10.1016/S2589-7500(22)00022-X.

2

Quantitative assessment of atherosclerotic plaque, recent progress and current limitations.定量评估动脉粥样硬化斑块：最新进展及当前局限。

J Cardiovasc Comput Tomogr. 2022 Mar-Apr;16(2):124-137. doi: 10.1016/j.jcct.2021.07.001. Epub 2021 Jul 16.

3

CT Evaluation by Artificial Intelligence for Atherosclerosis, Stenosis and Vascular Morphology (CLARIFY): A Multi-center, international study.