Cargando…
Detection of left ventricular systolic dysfunction from single-lead electrocardiography adapted for portable and wearable devices
Artificial intelligence (AI) can detect left ventricular systolic dysfunction (LVSD) from electrocardiograms (ECGs). Wearable devices could allow for broad AI-based screening but frequently obtain noisy ECGs. We report a novel strategy that automates the detection of hidden cardiovascular diseases,...
Autores principales: | Khunte, Akshay, Sangha, Veer, Oikonomou, Evangelos K., Dhingra, Lovedeep S., Aminorroaya, Arya, Mortazavi, Bobak J., Coppi, Andreas, Brandt, Cynthia A., Krumholz, Harlan M., Khera, Rohan |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10336107/ https://www.ncbi.nlm.nih.gov/pubmed/37433874 http://dx.doi.org/10.1038/s41746-023-00869-w |
Ejemplares similares
-
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) -
Biometric Contrastive Learning for Data-Efficient Deep Learning from Electrocardiographic Images
por: Sangha, Veer, et al.
Publicado: (2023) -
CarDS-Plus ECG Platform: Development and Feasibility Evaluation of a Multiplatform Artificial Intelligence Toolkit for Portable and Wearable Device Electrocardiograms
por: Shankar, Sumukh Vasisht, et al.
Publicado: (2023) -
An Evaluation of the Vulnerable Physician Workforce in the United States During the Coronavirus Disease-19 Pandemic
por: Khera, Rohan, et al.
Publicado: (2020) -
An Evaluation of the Vulnerable Physician Workforce in the USA During the Coronavirus Disease-19 Pandemic
por: Khera, Rohan, et al.
Publicado: (2020)