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

Advancements in artificial intelligence (AI) offer promising tools for improving diagnostic accuracy and patient outcomes in cardiovascular medicine. This study explores the potential of AI-assisted measurements in enhancing the prediction of major adverse cardiac events (MACE) in patients with cor...

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Autores principales:	Cheng Luo, Liang Mo, Zisan Zeng, Muliang Jiang, Bihong T. Chen
Formato:	Artigo
Lenguaje:	Inglês
Publicado:	Association of Basic Medical Sciences of Federation of Bosnia and Herzegovina 2024-04-01
Colección:	Biomolecules & Biomedicine
Materias:	Coronary computed tomography angiography (CCTA) artificial intelligence (AI) coronary artery disease (CAD) major adverse cardiac events (MACE)
Acceso en línea:	https://bjbms.org/ojs/index.php/bjbms/article/view/10497
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