At the COVID-19 pandemic onset, when individual-level data of COVID-19 patients were not
yet available, there was already a need for risk predictors to support prevention and …

Patients with severe COVID-19 have overwhelmed healthcare systems worldwide. We
hypothesized that machine learning (ML) models could be used to predict risks at different …

Background We investigated whether we could use influenza data to develop prediction
models for COVID-19 to increase the speed at which prediction models can reliably be …

Background The COVID-19 pandemic has affected millions of individuals and caused
hundreds of thousands of deaths worldwide. Predicting mortality among patients with COVID …

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 Coronavirus Disease 2019 is a pandemic that is straining healthcare resources,
mainly hospital beds. Multiple risk factors of disease progression requiring hospitalization …

Background Coronavirus disease 2019 (COVID-19) is sweeping the globe. Despite multiple
case-series, actionable knowledge to tailor decision-making proactively is missing …

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 …

Background COVID-19 pandemic has developed rapidly and the ability to stratify the most
vulnerable patients is vital. However, routinely used severity scoring systems are often low …

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 …