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Data-driven discovery of a clinical route for severity detection of COVID-19 paediatric cases

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摘要 In this retrospective COVID-19 study on 105 infected children admitted to Wuhan Children's Hospital,we have revealed two biomarkers(DBIL and ALT)to promptly screen out the severe ones from all the cases with the assistance of a proposed supervised decision-tree classifier.This clinical route achieves a 100%F1-score in the present investigation,which can be expected to facilitate early diagnosis and intervention for pediatric COVID-19 case.
出处 《IET Cyber-Systems and Robotics》 EI 2020年第4期205-206,共2页 智能系统与机器人(英文)
基金 supported by Wuhan Science and Technology Bureau Foundation under Grant 2017060201010161 the COVID-19 Prompt Response Research Special Project from Huazhong University of Science and Technology under Grant 2020kfyXGYJ113 and Grant 2020kfyXGYJ023 the National Natural Science Foundation of China under Grant 61991400 and Grant 61991403。
关键词 CASES admitted CLINICAL
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