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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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| 出版年: | ArXiv |
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| 主要な著者: | , , , , , , , , , , , , , , , |
| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
Cornell University
2021
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| 主題: | |
| オンライン・アクセス: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7805456/ https://ncbi.nlm.nih.gov/pubmed/33442560 |
| タグ: |
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