Prediction of criticality in patients with severe Covid-19 infection using three clinical features: a machine learning-based prognostic model with clinical data in Wuhan

L Yan, HT Zhang, Y Xiao, M Wang, Y Guo, C Sun… - MedRxiv, 2020 - medrxiv.org
The swift spread of COVID-19 epidemic has attracted worldwide attentions since Dec., 2019.
Till date, 77,041 confirmed Chinese cases have been reported by National Health …

[PDF][PDF] Prediction of survival for severe Covid-19 patients with three clinical features: development of a machine learning-based prognostic model with clinical data in …

L Yan, HT Zhang, Y Xiao, M Wang, C Sun, J Liang… - MedRxiv, 2020 - scholar.archive.org
The swift spread of COVID-19 epidemic has attracted worldwide attentions since Dec., 2019.
Till date, 77,041 confirmed Chinese cases have been reported by National Health …

A deep learning prognosis model help alert for COVID-19 patients at high-risk of death: a multi-center study

L Meng, D Dong, L Li, M Niu, Y Bai… - IEEE journal of …, 2020 - ieeexplore.ieee.org
Since its outbreak in December 2019, the persistent coronavirus disease (COVID-19)
became a global health emergency. It is imperative to develop a prognostic tool to identify …

[HTML][HTML] Early triage of critically ill COVID-19 patients using deep learning

W Liang, J Yao, A Chen, Q Lv, M Zanin, J Liu… - Nature …, 2020 - nature.com
The sudden deterioration of patients with novel coronavirus disease 2019 (COVID-19) into
critical illness is of major concern. It is imperative to identify these patients early. We show …

A tool for early prediction of severe coronavirus disease 2019 (COVID-19): a multicenter study using the risk nomogram in Wuhan and Guangdong, China

J Gong, J Ou, X Qiu, Y Jie, Y Chen… - Clinical infectious …, 2020 - academic.oup.com
Background Because there is no reliable risk stratification tool for severe coronavirus
disease 2019 (COVID-19) patients at admission, we aimed to construct an effective model …

Clinical and laboratory predictors of in-hospital mortality in patients with coronavirus disease-2019: a cohort study in Wuhan, China

K Wang, P Zuo, Y Liu, M Zhang, X Zhao… - Clinical infectious …, 2020 - academic.oup.com
Background This study aimed to develop mortality-prediction models for patients with
coronavirus disease-2019 (COVID-19). Methods The training cohort included consecutive …

[HTML][HTML] Development of a severity of disease score and classification model by machine learning for hospitalized COVID-19 patients

M Marcos, M Belhassen-García, A Sánchez-Puente… - PloS one, 2021 - journals.plos.org
Background Efficient and early triage of hospitalized Covid-19 patients to detect those with
higher risk of severe disease is essential for appropriate case management. Methods We …

Development and validation of prognosis model of mortality risk in patients with COVID-19

X Ma, M Ng, S Xu, Z Xu, H Qiu, Y Liu, J Lyu… - Epidemiology & …, 2020 - cambridge.org
This study aimed to identify clinical features for prognosing mortality risk using machine-
learning methods in patients with coronavirus disease 2019 (COVID-19). A retrospective …

Development and validation of a nomogram for assessing survival in patients with COVID-19 pneumonia

YM Dong, J Sun, YX Li, Q Chen, QQ Liu… - Clinical infectious …, 2021 - academic.oup.com
Background The outbreak of coronavirus disease 2019 (COVID-19) has spread worldwide
and continues to threaten peoples' health as well as put pressure on the accessibility of …

Early prediction of mortality risk among patients with severe COVID-19, using machine learning

C Hu, Z Liu, Y Jiang, O Shi, X Zhang… - International journal …, 2020 - academic.oup.com
Abstract Background Coronavirus disease 2019 (COVID-19), caused by severe acute
respiratory syndrome coronavirus 2 infection, has been spreading globally. We aimed to …