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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...
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 |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BMJ Publishing Group
2022
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Materias: | |
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 |
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