PubMed COVID-19 Clinical Care
1551 - 1560 of 7414 results found
COVID-19 Patient Count Prediction Using LSTM
Description
In December 2019, a pandemic named COVID-19 broke out in Wuhan, China, and in a few weeks, it spread to more than 200 countries worldwide. Every country infected with the disease started taking necessary measures to stop the spread and provide the
COVID-19 outbreak in Italy: an opportunity to evaluate extended interval dosing of ocrelizumab in MS patients
Description
INTRODUCTION: During the COVID-19 pandemic, ocrelizumab (OCR) infusions for MS patients were often re-scheduled because of MS center's disruption and concerns regarding immunosuppression. The aim of the present study was to assess changes in OCR
Characterisation and mitigation of gas leaks at laparoscopy: an international prospective, multi-center cohort clinical trial
Description
CONCLUSION: Laparoscopic gas leaks can be sensitively detected and consistently, effectively mitigated using straightforward available-now technology with most impact on the commonest, highest energy instrument exchange leaks.
CovTANet: A Hybrid Tri-Level Attention-Based Network for Lesion Segmentation, Diagnosis, and Severity Prediction of COVID-19 Chest CT Scans
Description
Rapid and precise diagnosis of COVID-19 is one of the major challenges faced by the global community to control the spread of this overgrowing pandemic. In this article, a hybrid neural network is proposed, named CovTANet, to provide an end-to-end
Correction
Description
No abstract
Combined positron emission tomography and contrast enhanced CT (PET/CeCT) is a feasible single investigation in the staging of oesophagogastric cancers: single-centre pilot study experience during the COVID-19 pandemic
Description
CONCLUSIONS: PET/CeCT allows accurate radiological staging of OG cancers with a single scan. Patients completed staging and started treatment faster, with a potential saving of £10,509 in one year. PET/CeCT has become standard staging at our trust
CovSegNet: A Multi Encoder-Decoder Architecture for Improved Lesion Segmentation of COVID-19 Chest CT Scans
Description
Automatic lung lesion segmentation of chest computer tomography (CT) scans is considered a pivotal stage toward accurate diagnosis and severity measurement of COVID-19. Traditional U-shaped encoder-decoder architecture and its variants suffer from
COVID-19 Pandemic is Associated With Increased Prevalence of GERD and Decreased GERD-related Quality of Life: Analysis From 9800 Participants in the Indonesian GERD-Q Study
Description
CONCLUSION: During the COVID-19 pandemic, the prevalence of GERD, heartburn, and those who reported impaired GERD-related quality of life increased. Regurgitation was the most common symptom reported by participants.
