Cargando…
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...
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: | |
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 |
Ejemplares similares
-
Biometric Contrastive Learning for Data-Efficient Deep Learning from Electrocardiographic Images
por: Sangha, Veer, et al.
Publicado: (2023) -
Detection of left ventricular systolic dysfunction from single-lead electrocardiography adapted for portable and wearable devices
por: Khunte, Akshay, et al.
Publicado: (2023) -
Use of Wearable Devices in Individuals With or at Risk for Cardiovascular Disease in the US, 2019 to 2020
por: Dhingra, Lovedeep S., et al.
Publicado: (2023) -
Automated Identification of Heart Failure with Reduced Ejection Fraction using Deep Learning-based Natural Language Processing
por: Nargesi, Arash A., et al.
Publicado: (2023) -
An explainable machine learning-based phenomapping strategy for adaptive predictive enrichment in randomized clinical trials
por: Oikonomou, Evangelos K., et al.
Publicado: (2023)