AIMC Topic: COVID-19

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Fast screening of COVID-19 inpatient samples by integrating machine learning and label-free SERS methods.

Analytica chimica acta
BACKGROUND: Advances in bio-analyte detection demonstrate the need for innovation to overcome the limitations of traditional methods. Emerging viruses evolve into variants, driving the need for fast screening to minimize the time required for positiv...

Quality assurance and validity of AI-generated single best answer questions.

BMC medical education
BACKGROUND: Recent advancements in generative artificial intelligence (AI) have opened new avenues in educational methodologies, particularly in medical education. This study seeks to assess whether generative AI might be useful in addressing the dep...

Machine learning-based prediction model for patients with recurrent Staphylococcus aureus bacteremia.

BMC medical informatics and decision making
BACKGROUND: Staphylococcus aureus bacteremia (SAB) remains a significant contributor to both community-acquired and healthcare-associated bloodstream infections. SAB exhibits a high recurrence rate and mortality rate, leading to numerous clinical tre...

Validation of a machine learning model for indirect screening of suicidal ideation in the general population.

Scientific reports
Suicide is among the leading causes of death worldwide and a concerning public health problem, accounting for over 700,000 registered deaths worldwide. However, suicide deaths are preventable with timely and evidence-based interventions, which are of...

Peptide classification landscape: An in-depth systematic literature review on peptide types, databases, datasets, predictors architectures and performance.

Computers in biology and medicine
Peptides are gaining significant attention in diverse fields such as the pharmaceutical market has seen a steady rise in peptide-based therapeutics over the past six decades. Peptides have been utilized in the development of distinct applications inc...

AI-MET: A deep learning-based clinical decision support system for distinguishing multisystem inflammatory syndrome in children from endemic typhus.

Computers in biology and medicine
The COVID-19 pandemic brought several diagnostic challenges, including the post-infectious sequelae multisystem inflammatory syndrome in children (MIS-C). Some of the clinical features of this syndrome can be found in other pathologies such as Kawasa...

A hybrid inception-dilated-ResNet architecture for deep learning-based prediction of COVID-19 severity.

Scientific reports
Chest computed tomography (CT) scans are essential for accurately assessing the severity of the novel Coronavirus (COVID-19), facilitating appropriate therapeutic interventions and monitoring disease progression. However, determining COVID-19 severit...

Predicting sleep quality among college students during COVID-19 lockdown using a LASSO-based neural network model.

BMC public health
BACKGROUND: In March 2022, a new outbreak of COVID-19 emerged in Quanzhou, leading to the implementation of strict lockdown management measures in colleges. While existing research has indicated that the pandemic has had a significant impact on sleep...

Disease diagnostics using machine learning of B cell and T cell receptor sequences.

Science (New York, N.Y.)
Clinical diagnosis typically incorporates physical examination, patient history, various laboratory tests, and imaging studies but makes limited use of the human immune system's own record of antigen exposures encoded by receptors on B cells and T ce...

RAG_MCNNIL6: A Retrieval-Augmented Multi-Window Convolutional Network for Accurate Prediction of IL-6 Inducing Epitopes.

Journal of chemical information and modeling
Interleukin-6 (IL-6) is a critical cytokine involved in immune regulation, inflammation, and the pathogenesis of various diseases, including autoimmune disorders, cancer, and the cytokine storm associated with severe COVID-19. Identifying IL-6 induci...