PubMed COVID-19 Clinical Care

Severely ill patients with COVID-19 are challenging to sedate and often require high-dose sedation and analgesic regimens. Ketamine can be an effective adjunct to facilitate sedation of critically ill patients but its effects on sedation level and

The Fv-antibodies were correponded to V(H) region of immunoglobulin G, which were composed of three complementarity determining regions (CDRs) for the specific binding of antigens. In this work, the Fv-antibodies against SARS-CoV-2 spike protein (SP)

BACKGROUND: Deep learning is a promising way to improve health care. Image-processing medical disciplines, such as pathology, are expected to be transformed by deep learning. The first clinically applicable deep-learning diagnostic support tools are

No abstract

CONCLUSION: We conclude that lower SNR and CNR on DIR-prepared T2* images originate from signal loss during DIR preparation and insufficient recovery between DIR preparation and image acquisition. Although, the impaired sensitivity can be recovered

CONCLUSIONS: Our findings indicate that most children hospitalized with COVID-19 have comorbidities. Younger age at admission and a longer hospital stay seem to be risk factors for readmission. In addition, the presence of cancer and impaired

In the ongoing global fight against coronavirus disease 2019 (COVID-19), the sample preparation process for real-time reverse transcription polymerase chain reaction (rRT-PCR) faces challenges due to time-consuming steps, labor-intensive procedures

Vaccines remain the cornerstone of medical prevention and are highly effective in reducing the risk of severe disease and death due to coronavirus disease 2019 (COVID-19). In the context of expanding the therapeutic armamentarium against COVID-19

While there have always been those in the American public who mistrust science and scientists' views of the world, they have tended to be a minority of the larger public. Recent COVID-19 related events indicate that could be changing for some key

The aim of the Social Media Mining for Health Applications (#SMM4H) shared tasks is to take a community-driven approach to address the natural language processing and machine learning challenges inherent to utilizing social media data for health