The recent outbreak of the coronavirus disease-2019 (COVID-19) caused serious challenges to the human society in China and across the world. COVID-19 induced pneumonia in human hosts and carried a highly inter-person contagiousness. The COVID-19 patients may carry severe symptoms, and some of them may even die of major organ failures. This study utilized the machine learning algorithms to build the COVID-19 severeness detection model. Support vector machine (SVM) demonstrated a promising detection accuracy after 32 features were detected to be significantly associated with the COVID-19 severeness. These 32 features were further screened for inter-feature redundancies. The final SVM model was trained using 28 features and achieved the overall accuracy 0.8148. This work may facilitate the risk estimation of whether the COVID-19 patients would develop the severe symptoms. The 28 COVID-19 severeness associated biomarkers may also be investigated for their underlining mechanisms how they were involved in the COVID-19 infections.
基金：
epidemiology, early warning and response techniques of major infectious diseases in the Belt and Road Initiative [2018ZX10101002]; National Natural Science Foundation of China [81871699]; Jilin Provincial Key Laboratory of Big Data Intelligent Computing [20180622002JC]; Education Department of Jilin Province [JJKH20180145KJ]; Foundation of Jilin Province Science and Technology Department [172408GH010234983]; Jilin University; Bioknow MedAI Institute [BMCPP-2018-001]; High Performance Computing Center of Jilin University; Fundamental Research Funds for the Central Universities, JLU
第一作者单位：[1]Jilin Univ, Dept Pathogenobiol, Coll Basic Med Sci, Key Lab Zoonosis,Chinese Minist Educ, Changchun, Peoples R China
通讯作者：
通讯机构：[3]Jilin Univ, Coll Software, BioKnow Hlth Informat Lab, Minist Educ, Changchun, Peoples R China[4]Jilin Univ, Key Lab Symbol Computat & Knowledge Engn, Minist Educ, Changchun, Peoples R China
推荐引用方式(GB/T 7714)：
Yao Haochen,Zhang Nan,Zhang Ruochi,et al.Severity Detection for the Coronavirus Disease 2019 (COVID-19) Patients Using a Machine Learning Model Based on the Blood and Urine Tests[J].FRONTIERS IN CELL AND DEVELOPMENTAL BIOLOGY.2020,8:doi:10.3389/fcell.2020.00683.
APA：
Yao, Haochen,Zhang, Nan,Zhang, Ruochi,Duan, Meiyu,Xie, Tianqi...&Wang, Guoqing.(2020).Severity Detection for the Coronavirus Disease 2019 (COVID-19) Patients Using a Machine Learning Model Based on the Blood and Urine Tests.FRONTIERS IN CELL AND DEVELOPMENTAL BIOLOGY,8,
MLA：
Yao, Haochen,et al."Severity Detection for the Coronavirus Disease 2019 (COVID-19) Patients Using a Machine Learning Model Based on the Blood and Urine Tests".FRONTIERS IN CELL AND DEVELOPMENTAL BIOLOGY 8.(2020)
