Contrastive learning improves critical event prediction in COVID-19 patients

Deep learning (DL) models typically require large-scale, balanced training data to be robust, generalizable, and effective in the context of healthcare. This has been a major issue for developing DL models for the coronavirus disease 2019 (COVID-19) pandemic, where data are highly class imbalanced....

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Detalles Bibliográficos
Autores principales: Wanyan, Tingyi, Honarvar, Hossein, Jaladanki, Suraj K., Zang, Chengxi, Naik, Nidhi, Somani, Sulaiman, De Freitas, Jessica K., Paranjpe, Ishan, Vaid, Akhil, Zhang, Jing, Miotto, Riccardo, Wang, Zhangyang, Nadkarni, Girish N., Zitnik, Marinka, Azad, Ariful, Wang, Fei, Ding, Ying, Glicksberg, Benjamin S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8542449/
https://www.ncbi.nlm.nih.gov/pubmed/34723227
http://dx.doi.org/10.1016/j.patter.2021.100389

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8542449/
https://www.ncbi.nlm.nih.gov/pubmed/34723227
http://dx.doi.org/10.1016/j.patter.2021.100389

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