PubMed COVID-19 Clinical Care

CONCLUSIONS: Our experiment proved that augmentations and masking could be important steps of data pre-processing and could contribute to improvement of the evaluation metrics. Because medical professionals often tend to lack confidence in AI-based

CONCLUSIONS: U.S. adults with comparatively worse self-rated health become more willing to see a NP for primary care when they hear information that raises their concerns about the local physician supply. The differences between the survey and

After February 2020, the majority of the world's governments decided to implement a lockdown in order to limit the spread of the deadly COVID-19 virus. This restriction improved air quality by reducing emissions of particular atmospheric pollutants

CONCLUSIONS: HAI increased during COVID-19. The microorganisms' susceptibility profile did not change with the pandemic, but the authors observed a disproportionate increase in large-spectrum antimicrobial drug use.

BACKGROUND: There is a clinical need for therapeutics for COVID-19 patients with acute hypoxemic respiratory failure whose 60-day mortality remains at 30-50%. Aviptadil, a lung-protective neuropeptide, and remdesivir, a nucleotide prodrug of an

We aimed to identify intergenerational solidarity (emotional closeness, in-person contact, phone contact, geographic proximity, consensus, and conflict) with digital communication (texting, video call, and social media interaction) with adult

CONCLUSIONS: Further research is needed on the long-term impacts of COVID-19 on ethnic minority communities. If policy responses to COVID-19 are to benefit ethnic minority communities, there is a need for future studies to consider fundamental

CONCLUSION: The effect of the COVID-19 pandemic on antenatal rates was significant for almost all the indicators studied. Future studies should focus on the impact of the pandemic on postnatal and immunization services on a national scale.

No abstract

COVID-19 is responsible for high mortality, but robust machine learning-based predictors of mortality are lacking. To generate a model for predicting mortality in patients hospitalized with COVID-19 using Gradient Boosting Decision Trees (GBDT). The