AIMC Topic: COVID-19 Vaccines
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Predictive analysis of COVID-19 occurrence and vaccination impacts across the 50 US states.
Computers in biology and medicine
Dec 3, 2024
OBJECTIVE: This study aimed to outline a machine learning model to assess the effectiveness of vaccination in COVID-19 confirmed cases and fatalities. The proposed model was evaluated using external validation to ensure optimal protection of vaccinat...
Integrating graph and reinforcement learning for vaccination strategies in complex networks.
Scientific reports
Dec 2, 2024
Pandemics like COVID-19 have a huge impact on human society and the global economy. Vaccines are effective in the fight against these pandemics but often in limited supplies, particularly in the early stages. Thus, it is imperative to distribute such...
Integrating Interpretability in Machine Learning and Deep Neural Networks: A Novel Approach to Feature Importance and Outlier Detection in COVID-19 Symptomatology and Vaccine Efficacy.
Viruses
Nov 29, 2024
In this study, we introduce a novel approach that integrates interpretability techniques from both traditional machine learning (ML) and deep neural networks (DNN) to quantify feature importance using global and local interpretation methods. Our meth...
Machine learning-enhanced immunopeptidomics applied to T-cell epitope discovery for COVID-19 vaccines.
Nature communications
Nov 28, 2024
Next-generation T-cell-directed vaccines for COVID-19 focus on establishing lasting T-cell immunity against current and emerging SARS-CoV-2 variants. Precise identification of conserved T-cell epitopes is critical for designing effective vaccines. He...
A deep learning approach predicting the activity of COVID-19 therapeutics and vaccines against emerging variants.
NPJ systems biology and applications
Nov 27, 2024
Understanding which viral variants evade neutralization is crucial for improving antibody-based treatments, especially with rapidly evolving viruses like SARS-CoV-2. Yet, conventional assays are labor intensive and cannot capture the full spectrum of...
Artificial intelligence meets the world experts; updates and novel therapies in autoimmunity - The 14th international congress on autoimmunity 2024 (AUTO14), Ljubljana.
Autoimmunity reviews
Nov 20, 2024
The bi-annual international congress on autoimmunity is a huge opportunity for the medical community to discuss the latest updates in the field. During the 14th congress 2024 (AUTO14) in Ljubljana, artificial intelligence (AI) occupied special attent...
Assessing COVID-19 Vaccine Effectiveness and Risk Factors for Severe Outcomes through Machine Learning Techniques: A Real-World Data Study in Andalusia, Spain.
Journal of epidemiology and global health
Nov 11, 2024
BACKGROUND: COVID-19 vaccination has become a pivotal global strategy in managing the pandemic. Despite COVID-19 no longer being classified as a Public Health Emergency of International Concern, the virus continues affecting people worldwide. This st...
Vaccine development using artificial intelligence and machine learning: A review.
International journal of biological macromolecules
Oct 18, 2024
The COVID-19 pandemic has underscored the critical importance of effective vaccines, yet their development is a challenging and demanding process. It requires identifying antigens that elicit protective immunity, selecting adjuvants that enhance immu...
COVID-19 vaccinations and their side effects: a scoping systematic review.
F1000Research
Sep 26, 2024
The COVID-19 virus has impacted people worldwide, causing significant changes in their lifestyles. Since the emergence of the epidemic, attempts have begun to prepare a vaccine that can eliminate the virus and restore balance to life in the entire w...
Cooperating Graph Neural Networks With Deep Reinforcement Learning for Vaccine Prioritization.
IEEE journal of biomedical and health informatics
Aug 6, 2024
This study explores the vaccine prioritization strategy to reduce the overall burden of the pandemic when the supply is limited. Existing vaccine distribution methods focus on macro-level or simplified micro-level assuming homogeneous behavior within...
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