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_60
Snippet: In conclusion, the assistant tool was built with 11 top-ranking clinical available blood indices that were extracted from the random forest algorithm. This result may capture the inherent patterns of these routine parameters to make routine blood tests play an influential role on the value of alarm diseases......
Document: In conclusion, the assistant tool was built with 11 top-ranking clinical available blood indices that were extracted from the random forest algorithm. This result may capture the inherent patterns of these routine parameters to make routine blood tests play an influential role on the value of alarm diseases.
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