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 …

Background Prioritizing patients in need of intensive care is necessary to reduce the
mortality rate during the COVID-19 pandemic. Although several scoring methods have been …

Background COVID-19 is a rapidly emerging respiratory disease caused by SARS-CoV-2.
Due to the rapid human-to-human transmission of SARS-CoV-2, many health care systems …

Background Patients with COVID-19 in the intensive care unit (ICU) have a high mortality
rate, and methods to assess patients' prognosis early and administer precise treatment are …

In the wake of COVID-19 disease, caused by the SARS-CoV-2 virus, we designed and
developed a predictive model based on Artificial Intelligence (AI) and Machine Learning …

Background The coronavirus disease (COVID-19) hospitalized patients are always at risk of
death. Machine learning (ML) algorithms can be used as a potential solution for predicting …

Background Several models have been developed to predict mortality in patients with
COVID-19 pneumonia, but only a few have demonstrated enough discriminatory capacity …

Background COVID-19 has infected millions of people worldwide and is responsible for
several hundred thousand fatalities. The COVID-19 pandemic has necessitated thoughtful …

Rationale Given the expanding number of COVID-19 cases and the potential for new waves
of infection, there is an urgent need for early prediction of the severity of the disease in …

The COVID-19 pandemic has been spreading worldwide since December 2019, presenting
an urgent threat to global health. Due to the limited understanding of disease progression …