Prehospital care plays a critical role in improving patient outcomes, particularly in cases of
time-sensitive emergencies such as trauma, cardiac failure, stroke, bleeding, breathing …

Background The application of machine learning (ML) to analyze clinical data with the goal
to predict patient outcomes has garnered increasing attention. Ensemble learning has been …

By applying AI techniques to a variety of pandemic-relevant data, artificial intelligence (AI)
has substantially supported the control of the spread of the SARS-CoV-2 virus. Along with …

Healthcare's evolution amid rapid scientific progress demands the efficient management of
extensive data. This has given rise to electronic health passports, which play a crucial role in …

Introduction Vaccines are the most important instrument for bringing the pandemic to a close
and saving lives and helping to reduce the risks of infection. It is important that everyone has …

Over the last few decades, globalization has driven up the demand for hospital Supply
Chain Management (SCM) with the goal of bio-medical development and improving …

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 …

Abstract Background and Aim In this study, a deep learning algorithm was used to predict
the survival rate of colon cancer (CC) patients, and compared its performance with …

When a patient is admitted to the hospital, they undergo monitoring and a variety of data is
collected. The continuous stream of clinical and analytical data provides a wealth of …

1 Introduction A novel outbreak of coronavirus emerged in Wuhan, China on December 31,
2019, and was referred to as 2019-nCoV or COVID-19, causing great concern among the …