Rapid and accurate identification of COVID-19 infection through machine learning based on clinical available blood test results

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

In this study, a total of 253 samples from 169 suspected patients were collected from multiple sources, Table 1 and the detailed information about the patients, including sex, age, and 49 parameters are listed in Table S1 . 105 consecutive samples from 27 patients with confirmed COVID-19 admitted to Lanzhou Pulmonary Hospital in Gansu Province were considered as positive samples and randomly divided into training set, test set, and external validation set. The virus nucleic acid assays (qRT-PCR) of throat swab and sputum samples were detected for all these patients to make a definite diagnosis. The diagnostic evidence for COVID-19 is based on World Health Organization interim guidance. Except for the COVID-19 samples, the remaining samples, which were collected from patients with similar symptoms or similar radiologic characteristic with COVID-19, including patients with common pneumonia, tuberculosis and lung cancer, were treated as negative samples. *Note：The number inside the bracket is the total number of patients where all the serial samples were collected . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.