Background In a pandemic, it is important for clinicians to stratify patients and decide who
receives limited medical resources. In this study, we used automated machine learning …

The global emergence of the unprecedented COVID-19 pandemic in late 2019 has led to
millions of infections and thousands of fatalities, profoundly affecting various aspects of life …

Background: The coronavirus disease 2019 (COVID-19) pandemic has affected over
millions of individuals and caused hundreds of thousands of deaths worldwide. It can be …

Background Accurate prediction of prognostic outcomes in patients with COVID-19 could
facilitate clinical decision-making and medical resource allocation. However, little is known …

(1) Background: Coronavirus disease 2019 (COVID-19) is a dominant, rapidly spreading
respiratory disease. However, the factors influencing COVID-19 mortality still have not been …

Background It's critical to identify COVID-19 patients with a higher death risk at early stage to
give them better hospitalization or intensive care. However, thus far, none of the machine …

The sudden increase of COVID-19 cases is putting a high pressure on healthcare services
worldwide. At the current stage, fast, accurate and early clinical assessment of the disease …

Background The recent pandemic of CoVID-19 has emerged as a threat to global health
security. There are very few prognostic models on CoVID-19 using machine learning …

Background During a pandemic, it is important for clinicians to stratify patients and decide
who receives limited medical resources. Machine learning models have been proposed to …

Abstract Coronavirus 2019 (COVID-19), caused by the SARS-CoV-2 virus, has become the
deadliest pandemic in modern history, reaching nearly every country worldwide and …