Relationship of age, atherosclerosis and angiographic stenosis using artificial intelligence

OBJECTIVE: The study evaluates the relationship of coronary stenosis, atherosclerotic plaque characteristics (APCs) and age using artificial intelligence enabled quantitative coronary computed tomographic angiography (AI-QCT). METHODS: This is a post-hoc analysis of data from 303 subjects enrolled i...

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Detalles Bibliográficos
Autores principales: Jonas, Rebecca, Earls, James, Marques, Hugo, Chang, Hyuk-Jae, Choi, Jung Hyun, Doh, Joon-Hyung, Her, Ae-Young, Koo, Bon Kwon, Nam, Chang-Wook, Park, Hyung-Bok, Shin, Sanghoon, Cole, Jason, Gimelli, Alessia, Khan, Muhammad Akram, Lu, Bin, Gao, Yang, Nabi, Faisal, Nakazato, Ryo, Schoepf, U Joseph, Driessen, Roel S, Bom, Michiel J, Thompson, Randall C, Jang, James J, Ridner, Michael, Rowan, Chris, Avelar, Erick, Généreux, Philippe, Knaapen, Paul, de Waard, Guus A, Pontone, Gianluca, Andreini, Daniele, Al-Mallah, Mouaz H, Jennings, Robert, Crabtree, Tami R, Villines, Todd C, Min, James K, Choi, Andrew D
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2021
Materias:
Coronary Artery Disease
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8596051/
https://www.ncbi.nlm.nih.gov/pubmed/34785589
http://dx.doi.org/10.1136/openhrt-2021-001832

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8596051/
https://www.ncbi.nlm.nih.gov/pubmed/34785589
http://dx.doi.org/10.1136/openhrt-2021-001832

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