AIMC Topic: COVID-19 Vaccines
Clear Filters Showing 1 to 10 of 79 articles
Modifiable risk factors of vaccine hesitancy: insights from a mixed methods multiple population study combining machine learning and thematic analysis during the COVID-19 pandemic.
BMC medicine
Mar 12, 2025
BACKGROUND: Vaccine hesitancy, the delay in acceptance or reluctance to vaccinate, ranks among the top threats to global health. Identifying modifiable factors contributing to vaccine hesitancy is crucial for developing targeted interventions to incr...
Artificial intelligence models predicting abnormal uterine bleeding after COVID-19 vaccination.
Scientific reports
Feb 27, 2025
The rapid deployment of COVID-19 vaccines has necessitated the ongoing surveillance of adverse events, with abnormal uterine bleeding (AUB) emerging as a reported concern in vaccinated females. We aimed to develop a machine learning (ML) model to pre...
Improving entity recognition using ensembles of deep learning and fine-tuned large language models: A case study on adverse event extraction from VAERS and social media.
Journal of biomedical informatics
Feb 7, 2025
OBJECTIVE: Adverse event (AE) extraction following COVID-19 vaccines from text data is crucial for monitoring and analyzing the safety profiles of immunizations, identifying potential risks and ensuring the safe use of these products. Traditional dee...
Humoral and cell-mediated immune responses to COVID-19 vaccines up to 6 months post three-dose primary series in adults with inborn errors of immunity and their breakthrough infections.
Frontiers in immunology
Jan 21, 2025
PURPOSE: Many individuals with inborn errors of immunity (IEIs) have poor humoral immune (HI) vaccine responses. Only a few studies have examined specific cell-mediated immune (CMI) responses to coronavirus disease 2019 (COVID-19) vaccines in this po...
Artificial intelligence-driven rational design of ionizable lipids for mRNA delivery.
Nature communications
Dec 30, 2024
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
Dec 4, 2024
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
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...
Stay Ahead of Medical AI
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.
Subscribe NowPopular Topics
- Machine Learning 30978
- Neural Networks, Computer 29696
- Algorithms 26813
- Deep Learning 26324
- Artificial Intelligence 24267
- Robotics 13307
- Image Processing, Computer-Assisted 9512
- Retrospective Studies 9097
- Magnetic Resonance Imaging 6173
- Reproducibility of Results 5589
- Tomography, X-Ray Computed 4765
- Support Vector Machine 4678
- Computational Biology 4229
- Brain 4045
- Computer Simulation 3877
Recent Journals
- Scientific reports 5865
- Sensors (Basel, Switzerland) 4794
- PloS one 4011
- Neural networks : the official journal of the International Neural Network Society 2928
- Computational intelligence and neuroscience 1931
- Computers in biology and medicine 1839
- Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference 1686
- Studies in health technology and informatics 1278
- IEEE journal of biomedical and health informatics 1129
- Journal of chemical information and modeling 994
- Nature communications 938
- Computer methods and programs in biomedicine 883
- Bioinformatics (Oxford, England) 861
- Briefings in bioinformatics 850
- IEEE transactions on neural networks and learning systems 823