AIMC Topic: SARS-CoV-2

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Utilizing machine learning to predict hospital admissions for pediatric COVID-19 patients (PrepCOVID-Machine).

Scientific reports
The COVID-19 pandemic has burdened healthcare systems globally. To curb high hospital admission rates, only patients with genuine medical needs are admitted. However, machine learning (ML) models to predict COVID-19 hospitalization in Asian children ...

The feasibility of using machine learning to predict COVID-19 cases.

International journal of medical informatics
BACKGROUND: Coronavirus Disease 2019 (COVID-19), caused by the SARS-CoV-2 virus, emerged as a global health crisis in 2019, resulting in widespread morbidity and mortality. A persistent challenge during the pandemic has been the accuracy of reported ...

Nanobody screening and machine learning guided identification of cross-variant anti-SARS-CoV-2 neutralizing heavy-chain only antibodies.

PLoS pathogens
Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) continues to persist, demonstrating the risks posed by emerging infectious diseases to national security, public health, and the economy. Development of new vaccines and antibodies for emer...

Interpretable COVID-19 chest X-ray detection based on handcrafted feature analysis and sequential neural network.

Computers in biology and medicine
Deep learning methods have significantly improved medical image analysis, particularly in detecting COVID-19 chest X-rays. Nonetheless, these methodologies frequently inhibit some drawbacks, such as limited interpretability, extensive computational r...

Robotic versus manual disinfection of global priority pathogens at COVID-19-dedicated hospitals.

American journal of infection control
BACKGROUND: Twelve bacterial families identified as global priority pathogens (GPPs) pose the greatest threat to human health due to declining antibiotic efficacy. Robotics, a swift and contactless tool for disinfecting hospital surfaces, was sought ...

Paying attention to the SARS-CoV-2 dialect : a deep neural network approach to predicting novel protein mutations.

Communications biology
Predicting novel mutations has long-lasting impacts on life science research. Traditionally, this problem is addressed through wet-lab experiments, which are often expensive and time consuming. The recent advancement in neural language models has pro...

Machine learning based prediction models for the prognosis of COVID-19 patients with DKA.

Scientific reports
Patients with Diabetic ketoacidosis (DKA) have increased critical illness and mortality during coronavirus diseases 2019 (COVID-19). The aim of our study was to develop a predictive model for the occurrence of critical illness and mortality in COVID-...

Humoral and cell-mediated immune responses to COVID-19 vaccines up to 6 months post three-dose primary series in adults with inborn errors of immunity and their breakthrough infections.

Frontiers in immunology
PURPOSE: Many individuals with inborn errors of immunity (IEIs) have poor humoral immune (HI) vaccine responses. Only a few studies have examined specific cell-mediated immune (CMI) responses to coronavirus disease 2019 (COVID-19) vaccines in this po...

Era of Generalist Conversational Artificial Intelligence to Support Public Health Communications.

Journal of medical Internet research
The integration of artificial intelligence (AI) into health communication systems has introduced a transformative approach to public health management, particularly during public health emergencies, capable of reaching billions through familiar digit...