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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....
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. |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2021
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Materias: | |
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 |
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