Biometric Contrastive Learning for Data-Efficient Deep Learning from Electrocardiographic Images

OBJECTIVE: Artificial intelligence (AI) detects heart disease from images of electrocardiograms (ECGs), however traditional supervised learning is limited by the need for large amounts of labeled data. We report the development of Biometric Contrastive Learning (BCL), a self-supervised pretraining a...

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Detalles Bibliográficos
Autores principales: Sangha, Veer, Khunte, Akshay, Holste, Gregory, Mortazavi, Bobak J, Wang, Zhangyang, Oikonomou, Evangelos K, 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/PMC10516080/
https://www.ncbi.nlm.nih.gov/pubmed/37745527
http://dx.doi.org/10.1101/2023.09.13.23295494

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10516080/
https://www.ncbi.nlm.nih.gov/pubmed/37745527
http://dx.doi.org/10.1101/2023.09.13.23295494

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