AIMC Topic: COVID-19
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Challenges on the implementation of wastewater-based epidemiology as a prediction tool: the paradigm of SARS-CoV-2.
The Science of the total environment
May 6, 2025
Wastewater Based Epidemiology (WBE) has been identified as a tool for monitoring and predicting patterns of SARS-CoV-2 in communities. Several factors may lead to a day-to-day variation in the measurement of viral genetic material. Wastewater samples...
MedFILIP: Medical Fine-Grained Language-Image Pre-Training.
IEEE journal of biomedical and health informatics
May 6, 2025
Medical vision-language pretraining (VLP) that leverages naturally-paired medical image-report data is crucial for medical image analysis. However, existing methods struggle to accurately characterize associations between images and diseases, leading...
AI designed, mutation resistant broad neutralizing antibodies against multiple SARS-CoV-2 strains.
Scientific reports
May 3, 2025
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
May 2, 2025
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
May 2, 2025
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 ...
Mapping the landscape: A bibliometric analysis of AI and teacher collaboration in educational research.
F1000Research
May 1, 2025
BACKGROUND: This study intends to investigate the relationship between artificial intelligence and teachers' collaboration in educational research in response to the growing use of technologies and the current status of the field.
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
Apr 30, 2025
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
Apr 30, 2025
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...
Multifractal analysis and support vector machine for the classification of coronaviruses and SARS-CoV-2 variants.
Scientific reports
Apr 29, 2025
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
Apr 29, 2025
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...
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