Machine learning based early warning system enables accurate mortality risk prediction for COVID-19
Methods to stratify patients according to mortality risk are essential to allocate limited heath resources during the COVID-19 crisis. Here, using machine learning methods, the authors present a mortality risk prediction model for COVID-19 that uses patients’ clinical data on admission to stratify p...
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Nature Portfolio
2020
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oai:doaj.org-article:53b866732ca841229e3c69def25e91782021-12-02T18:01:49ZMachine learning based early warning system enables accurate mortality risk prediction for COVID-1910.1038/s41467-020-18684-22041-1723https://doaj.org/article/53b866732ca841229e3c69def25e91782020-10-01T00:00:00Zhttps://doi.org/10.1038/s41467-020-18684-2https://doaj.org/toc/2041-1723Methods to stratify patients according to mortality risk are essential to allocate limited heath resources during the COVID-19 crisis. Here, using machine learning methods, the authors present a mortality risk prediction model for COVID-19 that uses patients’ clinical data on admission to stratify patients by mortality risk.Yue GaoGuang-Yao CaiWei FangHua-Yi LiSi-Yuan WangLingxi ChenYang YuDan LiuSen XuPeng-Fei CuiShao-Qing ZengXin-Xia FengRui-Di YuYa WangYuan YuanXiao-Fei JiaoJian-Hua ChiJia-Hao LiuRu-Yuan LiXu ZhengChun-Yan SongNing JinWen-Jian GongXing-Yu LiuLei HuangXun TianLin LiHui XingDing MaChun-Rui LiFei YeQing-Lei GaoNature PortfolioarticleScienceQENNature Communications, Vol 11, Iss 1, Pp 1-10 (2020) |
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DOAJ |
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EN |
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| spellingShingle |
Science Q Yue Gao Guang-Yao Cai Wei Fang Hua-Yi Li Si-Yuan Wang Lingxi Chen Yang Yu Dan Liu Sen Xu Peng-Fei Cui Shao-Qing Zeng Xin-Xia Feng Rui-Di Yu Ya Wang Yuan Yuan Xiao-Fei Jiao Jian-Hua Chi Jia-Hao Liu Ru-Yuan Li Xu Zheng Chun-Yan Song Ning Jin Wen-Jian Gong Xing-Yu Liu Lei Huang Xun Tian Lin Li Hui Xing Ding Ma Chun-Rui Li Fei Ye Qing-Lei Gao Machine learning based early warning system enables accurate mortality risk prediction for COVID-19 |
| description |
Methods to stratify patients according to mortality risk are essential to allocate limited heath resources during the COVID-19 crisis. Here, using machine learning methods, the authors present a mortality risk prediction model for COVID-19 that uses patients’ clinical data on admission to stratify patients by mortality risk. |
| format |
article |
| author |
Yue Gao Guang-Yao Cai Wei Fang Hua-Yi Li Si-Yuan Wang Lingxi Chen Yang Yu Dan Liu Sen Xu Peng-Fei Cui Shao-Qing Zeng Xin-Xia Feng Rui-Di Yu Ya Wang Yuan Yuan Xiao-Fei Jiao Jian-Hua Chi Jia-Hao Liu Ru-Yuan Li Xu Zheng Chun-Yan Song Ning Jin Wen-Jian Gong Xing-Yu Liu Lei Huang Xun Tian Lin Li Hui Xing Ding Ma Chun-Rui Li Fei Ye Qing-Lei Gao |
| author_facet |
Yue Gao Guang-Yao Cai Wei Fang Hua-Yi Li Si-Yuan Wang Lingxi Chen Yang Yu Dan Liu Sen Xu Peng-Fei Cui Shao-Qing Zeng Xin-Xia Feng Rui-Di Yu Ya Wang Yuan Yuan Xiao-Fei Jiao Jian-Hua Chi Jia-Hao Liu Ru-Yuan Li Xu Zheng Chun-Yan Song Ning Jin Wen-Jian Gong Xing-Yu Liu Lei Huang Xun Tian Lin Li Hui Xing Ding Ma Chun-Rui Li Fei Ye Qing-Lei Gao |
| author_sort |
Yue Gao |
| title |
Machine learning based early warning system enables accurate mortality risk prediction for COVID-19 |
| title_short |
Machine learning based early warning system enables accurate mortality risk prediction for COVID-19 |
| title_full |
Machine learning based early warning system enables accurate mortality risk prediction for COVID-19 |
| title_fullStr |
Machine learning based early warning system enables accurate mortality risk prediction for COVID-19 |
| title_full_unstemmed |
Machine learning based early warning system enables accurate mortality risk prediction for COVID-19 |
| title_sort |
machine learning based early warning system enables accurate mortality risk prediction for covid-19 |
| publisher |
Nature Portfolio |
| publishDate |
2020 |
| url |
https://doaj.org/article/53b866732ca841229e3c69def25e9178 |
| work_keys_str_mv |
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