Interoperator reliability of an on-site machine learning-based prototype to estimate CT angiography-derived fractional flow reserve

BACKGROUND: Advances in CT and machine learning have enabled on-site non-invasive assessment of fractional flow reserve (FFR(CT)). PURPOSE: To assess the interoperator and intraoperator variability of coronary CT angiography-derived FFR(CT) using a machine learning-based postprocessing prototype. MA...

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Detalles Bibliográficos
Autores principales: Han, Yushui, Ahmed, Ahmed Ibrahim, Schwemmer, Chris, Cocker, Myra, Alnabelsi, Talal S, Saad, Jean Michel, Ramirez Giraldo, Juan C, Al-Mallah, Mouaz H
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2022
Materias:
Coronary Artery Disease
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8938695/
https://www.ncbi.nlm.nih.gov/pubmed/35314508
http://dx.doi.org/10.1136/openhrt-2021-001951

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8938695/
https://www.ncbi.nlm.nih.gov/pubmed/35314508
http://dx.doi.org/10.1136/openhrt-2021-001951

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