Objectives Numerous people have died from coronavirus disease 2019 (COVID-19)
infection. Identifying crucial predictive biomarkers of disease mortality is critical to support …

The experience of the early nationwide COVID-19 pandemic in South Korea led to an early
shortage of medical resources. For efficient resource allocation, accurate prediction of the …

Background Prediction of mortality in patients with coronavirus disease 2019 (COVID-19) is
a key to improving the clinical outcomes, considering that the COVID-19 pandemic has led …

Background Early identification of patients with coronavirus disease 2019 (COVID-19) who
are at high risk of mortality is of vital importance for appropriate clinical decision making and …

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 …

Objective This study aimed to develop and externally validate a COVID-19 mortality risk
prediction algorithm. Design Retrospective cohort study. Setting Five designated tertiary …

Objective Many models for predicting various disease prognoses have achieved high
performance without laboratory test results. However, whether laboratory test results can …

Background To develop a sensitive and clinically applicable risk assessment tool identifying
coronavirus disease 2019 (COVID-19) patients with a high risk of mortality at hospital …

Objectives 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 …

In the current study, we aimed to develop and validate a model, based on our nationwide
centralized coronavirus disease 2019 (COVID‐19) database for predicting death. We …