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Predictive modeling of morbidity and mortality in COVID-19 hospitalized patients and its clinical implications.
Clinical activity of 3740 de-identified COVID-19 positive patients treated at NYU Langone Health (NYULH) were collected between January and August 2020. XGBoost model trained on clinical data from the final 24 hours excelled at predicting mortality (AUC=0.92, specificity=86% and sensitivity=85%). Re...
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| izdano v: | medRxiv |
|---|---|
| Main Authors: | , , , , , |
| Format: | Artigo |
| Jezik: | Inglês |
| Izdano: |
Cold Spring Harbor Laboratory
2021
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| Teme: | |
| Online dostop: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7724684/ https://ncbi.nlm.nih.gov/pubmed/33300013 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1101/2020.12.02.20235879 |
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