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A descriptive study of random forest algorithm for predicting COVID-19 patients outcome
BACKGROUND: The outbreak of coronavirus disease 2019 (COVID-19) that occurred in Wuhan, China, has become a global public health threat. It is necessary to identify indicators that can be used as optimal predictors for clinical outcomes of COVID-19 patients. METHODS: The clinical information from 12...
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| 出版年: | PeerJ |
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| 主要な著者: | , , , , , , , |
| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
PeerJ Inc.
2020
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| 主題: | |
| オンライン･アクセス: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7486830/ https://ncbi.nlm.nih.gov/pubmed/32974109 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.7717/peerj.9945 |
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