Clinical and inflammatory features based machine learning model for fatal risk prediction of hospitalized COVID-19 patients: results from a retrospective cohort study

Clinical and inflammatory features based machine learning model for fatal risk prediction of hospitalized COVID-19 patients: results from a retrospective cohort study

AbstractObjectives To appraise effective predictors for COVID-19 mortality in a retrospective cohort study.Methods A total of 1270 COVID-19 patients, including 984 admitted in Sino French New City Branch (training and internal validation sets randomly split at 7:3 ratio) and 286 admitted in Optical...

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Bibliographic Details
Main Authors: Xin Guan, Bo Zhang, Ming Fu, Mengying Li, Xu Yuan, Yaowu Zhu, Jing Peng, Huan Guo, Yanjun Lu
Format: Article
Language:English
Published: Taylor & Francis Group 2021-01-01
Series:Annals of Medicine
Subjects:
COVID-19
machine learning
fatal risk
extreme gradient boosting
Online Access:https://www.tandfonline.com/doi/10.1080/07853890.2020.1868564

Internet

https://www.tandfonline.com/doi/10.1080/07853890.2020.1868564

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