Data-driven discovery of a clinical route for severity detection of COVID-19 paediatric cases
Hui Yu, Yuqi Guo, Yun Xiang and 2 more
IET Cyber-systems and Robotics · 2020
doi:10.1049/iet-csr.2020.0037 (opens in a new tab)
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Abstract
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
Abstract licence: CC BY-ND
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