AIMC Topic: SARS-CoV-2

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AI designed, mutation resistant broad neutralizing antibodies against multiple SARS-CoV-2 strains.

Scientific reports
In this study, we developed a digital twin for SARS-CoV-2 by integrating diverse data and metadata with multiple data types and processing strategies, including machine learning, natural language processing, protein structural modeling, and protein s...

Neural networks to model COVID-19 dynamics and allocate healthcare resources.

Scientific reports
This study presents a neural network-based framework for COVID-19 transmission prediction and healthcare resource optimization. The model achieves high prediction accuracy by integrating epidemiological, mobility, vaccination, and environmental data ...

Boosting Convolution With Efficient MLP-Permutation for Volumetric Medical Image Segmentation.

IEEE transactions on medical imaging
Recently, the advent of Vision Transformer (ViT) has brought substantial advancements in 3D benchmarks, particularly in 3D volumetric medical image segmentation (Vol-MedSeg). Concurrently, multi-layer perceptron (MLP) network has regained popularity ...

Using machine learning involving diagnoses and medications as a risk prediction tool for post-acute sequelae of COVID-19 (PASC) in primary care.

BMC medicine
BACKGROUND: The aim of our study was to determine whether the application of machine learning could predict PASC by using diagnoses from primary care and prescribed medication 1 year prior to PASC diagnosis.

Use of Retrieval-Augmented Large Language Model for COVID-19 Fact-Checking: Development and Usability Study.

Journal of medical Internet research
BACKGROUND: The COVID-19 pandemic has been accompanied by an "infodemic," where the rapid spread of misinformation has exacerbated public health challenges. Traditional fact-checking methods, though effective, are time-consuming and resource-intensiv...

Identification and validation of programmed cell death related biomarkers for the treatment and prevention COVID-19.

Annals of medicine
PURPOSE: Programmed cell death (PCD) plays a key role in the progression of coronavirus disease 2019 (COVID-19). However, PCD-relevant biomarkers have not been fully discovered. The aim of this study was to explore the PCD-relevant biomarkers for the...

Multifractal analysis and support vector machine for the classification of coronaviruses and SARS-CoV-2 variants.

Scientific reports
This study presents a novel approach for the classification of coronavirus species and variants of SARS-CoV-2 using Chaos Game Representation (CGR) and 2D Multifractal Detrended Fluctuation Analysis (2D MF-DFA). By extracting fractal parameters from ...

A simple yet effective approach for predicting disease spread using mathematically-inspired diffusion-informed neural networks.

Scientific reports
The COVID-19 outbreak has highlighted the importance of mathematical epidemic models like the Susceptible-Infected-Recovered (SIR) model, for understanding disease spread dynamics. However, enhancing their predictive accuracy complicates parameter es...

Introduction to WBE case estimation: A practical toolset for public health practitioners.

The Science of the total environment
Public health practitioners can use wastewater data to grasp disease dynamics, including incidence, prevalence, and potential disease trajectory. The expertise required to analyze and interpret wastewater data exceed those of most entry-level epidemi...

Predictive models of severe disease in patients with COVID-19 pneumonia at an early stage on CT images using topological properties.

Radiological physics and technology
Prediction of severe disease (SVD) in patients with coronavirus disease (COVID-19) pneumonia at an early stage could allow for more appropriate triage and improve patient prognosis. Moreover, the visualization of the topological properties of COVID-1...