PubMed COVID-19 Clinical Care

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

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

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

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

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

The COVID-19 pandemic was met with rapid, unprecedented global collaboration and action. Even still, the public health, societal, and economic impact may be felt for years to come. The risk of another pandemic occurring in the next few decades is

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