… and developed a predictive model based on … predict the mortality risk of patients with
COVID-19. In this study, we used a dataset of more than 2,670,000 laboratory-confirmed COVID-19 …

… Our model … , the model is able to stratify COVID-19 patients into low-, medium- and high-risk
groups for developing severe illness. We propose that this model, with its higher prediction …

… clinical features that contributed the most to this prediction. An improved understanding of
predictive factors for COVID-19 … of support systems for clinical decision making that can better …

… prediction model for COVID-19 based on ML algorithms that utilize patients’ routine clinical
… What are the most relevant predictors of mortality among COVID-19 in-hospital patients? (2) …

… main aim of prediction models is to support medical decision making in individual patients.
Therefore, it is vital to identify a target setting in which predictions serve a clinical need (eg, …

… in predicting COVID-19 severity [9–11]. Here we report a predictive model and a risk score
system to predict … and in-hospital mortality in laboratory-confirmed COVID-19 patients. This …

… Supervised learning is a process in which the predictive models are … predicted labels
or values computed from the estimated model (for this work, positive or negative for COVID-19…

… early clinical assessment of the disease severity is vital. To support decision making and …
of Wuhan, China, to identify crucial predictive biomarkers of disease mortality. For this purpose, …

… prediction tool in our possession. Therefore, the aim of this study is to test the capabilities of
ML models for the triage of patients with COVID-19… or risk-score prediction models. The poor-…

… Due to such limitations, the need for clinical decisions making system with predictive …
In this study, we develop and evaluate clinical predictive models to determine the COVID-19 …