학술논문
Human versus Artificial Intelligence–Based Echocardiographic Analysis as a Predictor of Outcomes: An Analysis from the World Alliance Societies of Echocardiography COVID Study
Document Type
Article
Author
Asch, Federico M.; Descamps, Tine; Sarwar, Rizwan; Karagodin, Ilya; Singulane, Cristiane Carvalho; Xie, Mingxing; Tucay, Edwin S.; Tude Rodrigues, Ana C.; Vasquez-Ortiz, Zuilma Y.; Monaghan, Mark J.; Ordonez Salazar, Bayardo A.; Soulat-Dufour, Laurie; Alizadehasl, Azin; Mostafavi, Atoosa; Moreo, Antonella; Citro, Rodolfo; Narang, Akhil; Wu, Chun; Addetia, Karima; Upton, Ross; Woodward, Gary M.; Lang, Roberto M.; Munoz, Vince Ryan V.; De Marchi, Rafael Porto; Alday-Ramirez, Sergio M.; Orihuela, Consuelo; Sadeghpour, Anita; Breeze, Jonathan; Hoare, Amy; Rosales, Carlos Ixcanparij; Cohen, Ariel; Milani, Martina; Trolese, Ilaria; Belli, Oriana; De Chiara, Benedetta; Bellino, Michele; Iuliano, Giuseppe; Yang, Yun
Source
Journal of the American Society of Echocardiography; December 2022, Vol. 35 Issue: 12 p1226-1237.e7
Subject
Language
ISSN
08947317; 10976795
Abstract
Transthoracic echocardiography is the leading cardiac imaging modality for patients admitted with COVID-19, a condition of high short-term mortality. The aim of this study was to test the hypothesis that artificial intelligence (AI)–based analysis of echocardiographic images could predict mortality more accurately than conventional analysis by a human expert.