Current evidence on COVID-19 prognostic models is inconsistent and clinical applicability
remains controversial. We performed a systematic review to summarize and critically …

Introduction Since the beginning of the COVID-19 pandemic, numerous machine and deep
learning (MDL) methods have been proposed in the literature to analyze patient …

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 …

Community-acquired pneumonia (CAP) is accountable for high mortality in both pediatric
and adult populations worldwide, about one-third of hospitalized patients pass away within a …

Background: The declaration of the COVID-19 pandemic triggered global efforts to control
and manage the virus impact. Scientists and researchers have been strongly involved in …

Since its emergence, the COVID-19 pandemic still poses a major global health threat. In this
setting, a number of useful machine learning applications have been explored to assist …

From the moment a patient is admitted to the hospital, monitoring begins, and specific
information is collected. The continuous flow of parameters, including clinical and analytical …

Forensic economics is a relatively new branch on the intersection of the economics and
forensics at least. The separate use of the artificial intelligence in law, forensic, and …

Introduction: The COVID-19 pandemic has changed the immunological status of the
population, indicating increased activation. The aim of the study was to compare the degree …

This work focuses on the problem of mortality prediction in patients with pneumonia after
admission into an intensive care unit, by addressing it via logistic regression. This approach …