Predicting post-operative right ventricular failure using video-based deep learning

The echocardiogram allows for a comprehensive assessment of the cardiac musculature and valves, but its rich temporally resolved data remain underutilized. Here, the authors develop a video AI system trained to predict post-operative right ventricular failure.

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Autores principales:	Rohan Shad, Nicolas Quach, Robyn Fong, Patpilai Kasinpila, Cayley Bowles, Miguel Castro, Ashrith Guha, Erik E. Suarez, Stefan Jovinge, Sangjin Lee, Theodore Boeve, Myriam Amsallem, Xiu Tang, Francois Haddad, Yasuhiro Shudo, Y. Joseph Woo, Jeffrey Teuteberg, John P. Cunningham, Curtis P. Langlotz, William Hiesinger
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Science Q
Acceso en línea:	https://doaj.org/article/b505d01868f146ffbab6d3814a231757
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spelling	oai:doaj.org-article:b505d01868f146ffbab6d3814a2317572021-12-02T15:26:52ZPredicting post-operative right ventricular failure using video-based deep learning10.1038/s41467-021-25503-92041-1723https://doaj.org/article/b505d01868f146ffbab6d3814a2317572021-08-01T00:00:00Zhttps://doi.org/10.1038/s41467-021-25503-9https://doaj.org/toc/2041-1723The echocardiogram allows for a comprehensive assessment of the cardiac musculature and valves, but its rich temporally resolved data remain underutilized. Here, the authors develop a video AI system trained to predict post-operative right ventricular failure.Rohan ShadNicolas QuachRobyn FongPatpilai KasinpilaCayley BowlesMiguel CastroAshrith GuhaErik E. SuarezStefan JovingeSangjin LeeTheodore BoeveMyriam AmsallemXiu TangFrancois HaddadYasuhiro ShudoY. Joseph WooJeffrey TeutebergJohn P. CunninghamCurtis P. LanglotzWilliam HiesingerNature PortfolioarticleScienceQENNature Communications, Vol 12, Iss 1, Pp 1-8 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Science Q
spellingShingle	Science Q Rohan Shad Nicolas Quach Robyn Fong Patpilai Kasinpila Cayley Bowles Miguel Castro Ashrith Guha Erik E. Suarez Stefan Jovinge Sangjin Lee Theodore Boeve Myriam Amsallem Xiu Tang Francois Haddad Yasuhiro Shudo Y. Joseph Woo Jeffrey Teuteberg John P. Cunningham Curtis P. Langlotz William Hiesinger Predicting post-operative right ventricular failure using video-based deep learning
description	The echocardiogram allows for a comprehensive assessment of the cardiac musculature and valves, but its rich temporally resolved data remain underutilized. Here, the authors develop a video AI system trained to predict post-operative right ventricular failure.
format	article
author	Rohan Shad Nicolas Quach Robyn Fong Patpilai Kasinpila Cayley Bowles Miguel Castro Ashrith Guha Erik E. Suarez Stefan Jovinge Sangjin Lee Theodore Boeve Myriam Amsallem Xiu Tang Francois Haddad Yasuhiro Shudo Y. Joseph Woo Jeffrey Teuteberg John P. Cunningham Curtis P. Langlotz William Hiesinger
author_facet	Rohan Shad Nicolas Quach Robyn Fong Patpilai Kasinpila Cayley Bowles Miguel Castro Ashrith Guha Erik E. Suarez Stefan Jovinge Sangjin Lee Theodore Boeve Myriam Amsallem Xiu Tang Francois Haddad Yasuhiro Shudo Y. Joseph Woo Jeffrey Teuteberg John P. Cunningham Curtis P. Langlotz William Hiesinger
author_sort	Rohan Shad
title	Predicting post-operative right ventricular failure using video-based deep learning
title_short	Predicting post-operative right ventricular failure using video-based deep learning
title_full	Predicting post-operative right ventricular failure using video-based deep learning
title_fullStr	Predicting post-operative right ventricular failure using video-based deep learning
title_full_unstemmed	Predicting post-operative right ventricular failure using video-based deep learning
title_sort	predicting post-operative right ventricular failure using video-based deep learning
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/b505d01868f146ffbab6d3814a231757
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Predicting post-operative right ventricular failure using video-based deep learning

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