An interpretable machine learning model based on a quick pre-screening system enables accurate deterioration risk prediction for COVID-19
Abstract A high-performing interpretable model is proposed to predict the risk of deterioration in coronavirus disease 2019 (COVID-19) patients. The model was developed using a cohort of 3028 patients diagnosed with COVID-19 and exhibiting common clinical symptoms that were internally verified (AUC...
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| Auteurs principaux: | , , , , , , , , , , , , , , , , , |
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| Format: | article |
| Langue: | EN |
| Publié: |
Nature Portfolio
2021
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| Sujets: | |
| Accès en ligne: | https://doaj.org/article/c181bf448c074d5eb8ad5f7c833512ad |
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