Aim To perform a systematic review on the use of Artificial Intelligence (AI) techniques for
predicting COVID-19 hospitalization and mortality using primary and secondary data …

The development of artificial intelligence (AI) allows for the construction of technologies
capable of implementing functions that represent the human mind, senses, and problem …

Background The clinical spectrum of acute SARS-CoV-2 infection ranges from an
asymptomatic to life-threatening disease. Considering the broad spectrum of severity …

Objective This study aims to design, validate and assess the accuracy a deep learning
model capable of differentiation Chest X-Rays between pneumonia, acute respiratory …

Respiratory failure (RF) is a frequent occurrence in critically ill patients and is associated
with significant morbidity and mortality as well as resource use. To improve the monitoring …

Critical care medicine in the 21st century has witnessed remarkable advancements that
have significantly improved patient outcomes in intensive care units (ICUs). This abstract …

In situations like the COVID-19 pandemic, healthcare systems are under enormous pressure
as they can rapidly collapse under the burden of the crisis. Machine learning (ML) based risk …

Over the course of the past ten years, there has been a rising interest in the application of AI
in radiology with the goal of improving diagnostic practises. Every stage of the imaging …

Aim Acute respiratory distress syndrome or ARDS is an acute, severe form of respiratory
failure characterised by poor oxygenation and bilateral pulmonary infiltrates. Advancements …

Background Although the prevalence of childhood illnesses has significantly decreased,
acute respiratory infections continue to be the leading cause of death and disease among …