PubMed COVID-19 Clinical Care

To evaluate the diagnostic performance of our deep learning (DL) model of COVID-19 and investigate whether the diagnostic performance of radiologists was improved by referring to our model. Our datasets contained chest X-rays (CXRs) for the following

CONCLUSIONS: Prior investments in aligning systems provided unanticipated benefits for organizational and community resilience during the COVID-19 pandemic. Our results illustrate a pathway for investment in system alignment efforts that build

No abstract

Since SARS-CoV-2 spread through China at the end of 2019, COVID-19 has been probably the most difficult challenge in the last decades for healthcare systems all around the world, still representing a danger for fragile patients with different

Louis, Alexandre, Charlotte Pröpper, Yann Savina, Corentin Tanne, Guy Duperrex, Paul Robach, Pascal Zellner, Stéphane Doutreleau, Jean-Michel Boulet, Alain Frey, Fabien Pillard, Cristina Pistea, Mathias Poussel, Thomas Thuet, Jean-Paul Richalet, and

CONCLUSIONS: Our study has shown that Ureaplasma species have reached a significant prevalence in China and demands adequate attention.

CONCLUSIONS: The new Omicron variant BA.2.86 has affected 264 people in 23 countries. The disease is more common in females than males and mainly affects old age people (over 60 years of age). However, no deaths have been reported. The variant is

Recent years have seen a lot of interest in mycosporine-like amino acids (MAAs) because of their alleged potential as a natural microbial sunscreen. Since chemical ultraviolet (UV) absorbers are unsafe for long-term usage, the demand for natural UV

INTRODUCTION: Despite growing awareness of post-COVID-19 cholangiopathy as one of the most serious long-term gastrointestinal consequences of COVID-19, the endoscopic features of this disease are still poorly characterized. This study aimed to more

High-throughput technologies and machine learning (ML), when applied to a huge pool of medical data such as omics data, result in efficient analysis. Recent research aims to apply and develop ML models to predict a disease well in time using