Cargando…
Enhancing convolutional neural network predictions of electrocardiograms with left ventricular dysfunction using a novel sub-waveform representation
BACKGROUND: Electrocardiogram (ECG) deep learning (DL) has promise to improve the outcomes of patients with cardiovascular abnormalities. In ECG DL, researchers often use convolutional neural networks (CNNs) and traditionally use the full duration of raw ECG waveforms that create redundancies in fea...
Autores principales: | Honarvar, Hossein, Agarwal, Chirag, Somani, Sulaiman, Vaid, Akhil, Lampert, Joshua, Wanyan, Tingyi, Reddy, Vivek Y., Nadkarni, Girish N., Miotto, Riccardo, Zitnik, Marinka, Wang, Fei, Glicksberg, Benjamin S. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9596304/ https://www.ncbi.nlm.nih.gov/pubmed/36310683 http://dx.doi.org/10.1016/j.cvdhj.2022.07.074 |
Ejemplares similares
-
Contrastive learning improves critical event prediction in COVID-19 patients
por: Wanyan, Tingyi, et al.
Publicado: (2021) -
Deep learning and the electrocardiogram: review of the current state-of-the-art
por: Somani, Sulaiman, et al.
Publicado: (2021) -
A foundational vision transformer improves diagnostic performance for electrocardiograms
por: Vaid, Akhil, et al.
Publicado: (2023) -
Multi-center retrospective cohort study applying deep learning to electrocardiograms to identify left heart valvular dysfunction
por: Vaid, Akhil, et al.
Publicado: (2023) -
Deep Learning on Electrocardiograms for Prediction of In-hospital Intradialytic Hypotension in Patients with ESKD
por: Vaid, Akhil, et al.
Publicado: (2023)