PubMed COVID-19 Clinical Care

CONCLUSION: This review demonstrates that critical care publicly available data used to train AI algorithms do not include enough information to properly look for intrinsic bias and fairness issues towards historically marginalized populations.

BACKGROUND: Dyspnea and fatigue are characteristics of long SARS-CoV-2 (COVID)-19. Cardiopulmonary exercise testing (CPET) can be used to better evaluate such patients.

ObjectiveNursing workplace injuries related to staff-assisted patient/resident movement occur frequently, however, little is known about the programs that aim to prevent these injuries. The objectives of this study were to: (i) describe how

Fusion with host cell membrane is the main mechanism of infection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Here, we propose that a new strategy to screen small-molecule antagonists blocking SARS-CoV-2 membrane fusion. Using

CONCLUSIONS: The boosting model, which excels in producing classification models using categorical data, excels in developing classification models using linear numerical data, such as laboratory tests. Finally, the proposed model can be applied in

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There is still much to uncover regarding the molecular details of SARS-CoV-2 infection. As the most abundant protein, coronavirus nucleocapsid (N) protein encapsidates viral RNAs, serving as the structural component of ribonucleoprotein and virion

BACKGROUND: Rome criteria differentiate distinct types of disorders of gut-brain interaction (DGBI); also known as functional gastrointestinal disorders. Overlap of symptom categories frequently occurs. This systematic review and meta-analysis aimed

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The COVID-19 pandemic has highlighted a significant research gap in the field of molecular diagnostics. This has brought forth the need for AI-based edge solutions that can provide quick diagnostic results whilst maintaining data privacy, security