Objective To review and appraise the validity and usefulness of published and preprint
reports of prediction models for prognosis of patients with covid-19, and for detecting people …

In late December 2019, a new type of coronavirus was discovered, which was later named
severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Since its discovery, the …

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 …

The worldwide health crisis caused by the SARS-Cov-2 virus has resulted in more than 3
million deaths so far. Improving early screening, diagnosis and prognosis of the disease are …

The recent COVID-19 pandemic has affected health systems across the world. Especially,
Intensive Care Units (ICUs) have played a pivotal role in the treatment of critically-ill patients …

Background and Aims The aim of this study was to apply machine learning models and a
nomogram to differentiate critically ill from non-critically ill COVID-19 pneumonia patients …

Since the beginning of the COVID-19 pandemic, new and non-invasive digital technologies
such as artificial intelligence (AI) had been introduced for mortality prediction of COVID-19 …

Background Throughout 2020, the coronavirus disease 2019 (COVID‐19) has become a
threat to public health on national and global level. There has been an immediate need for …

Background: Severity of illness scores—Acute Physiology and Chronic Health Evaluation,
Simplified Acute Physiology Score, and Sequential Organ Failure Assessment—are current …

The COVID-19 outbreak is currently one of the biggest challenges facing countries around
the world. Millions of people have lost their lives due to COVID-19. Therefore, the accurate …