A digital biomarker for aortic stenosis development and progression using deep learning for two-dimensional echocardiography

BACKGROUND: The timely identification of aortic stenosis (AS) and disease stage that merits intervention requires frequent echocardiography. However, there is no strategy to personalize the frequency of monitoring needed. OBJECTIVES: To explore the role of AI-enhanced two-dimensional-echocardiograph...

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Detalles Bibliográficos
Autores principales: Oikonomou, Evangelos K., Holste, Gregory, Yuan, Neal, Coppi, Andreas, McNamara, Robert L., Haynes, Norrisa, Vora, Amit N., Velazquez, Eric J., Li, Fan, Menon, Venu, Kapadia, Samir R., Gill, Thomas M, Nadkarni, Girish N., Krumholz, Harlan M., Wang, Zhangyang, Ouyang, David, Khera, Rohan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cold Spring Harbor Laboratory 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10557799/
https://www.ncbi.nlm.nih.gov/pubmed/37808685
http://dx.doi.org/10.1101/2023.09.28.23296234

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10557799/
https://www.ncbi.nlm.nih.gov/pubmed/37808685
http://dx.doi.org/10.1101/2023.09.28.23296234

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