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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I publikationen:ArXiv
Huvudupphovsmän: 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.
Materialtyp: Artigo
Språk:Inglês
Publicerad: Cornell University 2021
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Article
Länkar:https://ncbi.nlm.nih.gov/pmc/articles/PMC7805456/
https://ncbi.nlm.nih.gov/pubmed/33442560
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