Clinical validation of an artificial intelligence-assisted algorithm for automated quantification of left ventricular ejection fraction in real time by a novel handheld ultrasound device

AIMS: We sought to evaluate the reliability and diagnostic accuracy of a novel handheld ultrasound device (HUD) with artificial intelligence (AI) assisted algorithm to automatically calculate ejection fraction (autoEF) in a real-world patient population. METHODS AND RESULTS: We studied 100 consecuti...

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Detalles Bibliográficos
Autores principales: Papadopoulou, Stella-Lida, Sachpekidis, Vasileios, Kantartzi, Vasiliki, Styliadis, Ioannis, Nihoyannopoulos, Petros
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2022
Materias:
Original Articles
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9707920/
https://www.ncbi.nlm.nih.gov/pubmed/36713988
http://dx.doi.org/10.1093/ehjdh/ztac001

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9707920/
https://www.ncbi.nlm.nih.gov/pubmed/36713988
http://dx.doi.org/10.1093/ehjdh/ztac001

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