Contrastive Learning Improves Critical Event Prediction in COVID-19 Patients

Machine Learning (ML) 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 ML models for the coronavirus-disease 2019 (COVID-19) pandemic where data is highly imbalanced, parti...

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Enregistré dans:
Détails bibliographiques
Publié dans:ArXiv
Auteurs principaux: Wanyan, Tingyi, Honarvar, Hossein, Jaladanki, Suraj K., Zang, Chengxi, Naik, Nidhi, Somani, Sulaiman, Freitas, Jessica K. De, Paranjpe, Ishan, Vaid, Akhil, Miotto, Riccardo, Nadkarni, Girish N., Zitnik, Marinka, ArifulAzad, Wang, Fei, Ding, Ying, Glicksberg, Benjamin S.
Format: Artigo
Langue:Inglês
Publié: Cornell University 2021
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Article
Accès en ligne:https://ncbi.nlm.nih.gov/pmc/articles/PMC7805456/
https://ncbi.nlm.nih.gov/pubmed/33442560
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