Author: Jiangpeng Wu; Pengyi Zhang; Liting Zhang; Wenbo Meng; Junfeng Li; Chongxiang Tong; Yonghong Li; Jing Cai; Zengwei Yang; Jinhong Zhu; Meie Zhao; Huirong Huang; Xiaodong Xie; Shuyan Li
Title: Rapid and accurate identification of COVID-19 infection through machine learning based on clinical available blood test results Document date: 2020_4_6
ID: kjovtgua_29
Snippet: Under the guidance of the outstanding performance, the final model was built based on the sophisticated combination of 11 selected parameters. According to the performance requirements, the value of cutoff was adjusted to 0· 43. The external validation set with 11 laboratory parameters also didn't participate in any modeling process and was only used to reconsider the reliability of the model,.....
Document: Under the guidance of the outstanding performance, the final model was built based on the sophisticated combination of 11 selected parameters. According to the performance requirements, the value of cutoff was adjusted to 0· 43. The external validation set with 11 laboratory parameters also didn't participate in any modeling process and was only used to reconsider the reliability of the model,
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