AIMC Topic: COVID-19 Vaccines

Clear Filters Showing 21 to 30 of 96 articles

Artificial intelligence-driven rational design of ionizable lipids for mRNA delivery.

Nature communications
Lipid nanoparticles (LNPs) have proven effective in mRNA delivery, as evidenced by COVID-19 vaccines. Its key ingredient, ionizable lipids, is traditionally optimized by inefficient and costly experimental screening. This study leverages artificial i...

Using machine learning for personalized prediction of longitudinal coronavirus disease 2019 vaccine responses in transplant recipients.

American journal of transplantation : official journal of the American Society of Transplantation and the American Society of Transplant Surgeons
The coronavirus disease 2019 pandemic has underscored the importance of vaccines, especially for immunocompromised populations like solid organ transplant recipients, who often have weaker immune responses. The purpose of this study was to compare de...

Predictive analysis of COVID-19 occurrence and vaccination impacts across the 50 US states.

Computers in biology and medicine
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
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
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
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
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
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
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
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...