AIMC Topic: Vaccines
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Can Natural Language Processing Improve the Efficiency of Vaccine Adverse Event Report Review?
Methods of information in medicine
Sep 23, 2015
BACKGROUND: Individual case review of spontaneous adverse event (AE) reports remains a cornerstone of medical product safety surveillance for industry and regulators. Previously we developed the Vaccine Adverse Event Text Miner (VaeTM) to offer autom...
Mapping the landscape of AI and ML in vaccine innovation: A bibliometric study.
Human vaccines & immunotherapeutics
Dec 1, 2025
With the rapid advancement of artificial intelligence (AI) and machine learning (ML) technologies, their applications in the medical field have expanded significantly. Particularly in vaccine innovation, AI and ML have shown considerable potential. T...
Unveiling differential adverse event profiles in vaccines via LLM text embeddings and ontology semantic analysis.
Journal of biomedical semantics
May 23, 2025
BACKGROUND: Vaccines are crucial for preventing infectious diseases; however, they may also be associated with adverse events (AEs). Conventional analysis of vaccine AEs relies on manual review and assignment of AEs to terms in terminology or ontolog...
Highlights From IDWeek 2023-New Vaccines, Artificial Intelligence, and Antimicrobial Resistance.
JAMA
Dec 5, 2023
Vaxi-DL: An Artificial Intelligence-Enabled Platform for Vaccine Development.
Methods in molecular biology (Clifton, N.J.)
Jan 1, 2023
Vaccine development is a complex and long process. It involves several steps, including computational studies, experimental analyses, animal model system studies, and clinical trials. This process can be accelerated by using in silico antigen screeni...
Computer Aided Reverse Vaccinology: A Game-changer Approach for Vaccine Development.
Combinatorial chemistry & high throughput screening
Jan 1, 2023
One of the most dynamic approaches in biotechnology is reverse vaccinology, which plays a huge role in today's developing vaccines. It has the capability of exploring and identifying the most potent vaccine candidate in a limited period of time. The ...
Inference Time of a CamemBERT Deep Learning Model for Sentiment Analysis of COVID Vaccines on Twitter.
Studies in health technology and informatics
Jun 29, 2022
In previous work, we implemented a deep learning model with CamemBERT and PyTorch, and built a microservices architecture using the TorchServe serving library. Without TorchServe, inference time was three times faster when the model was loaded once i...
Artificial Intelligence for Vaccine Design.
Methods in molecular biology (Clifton, N.J.)
Jan 1, 2022
Often likened to "the new electricity," artificial intelligence (AI) has broad and sweeping impact in many areas. Perhaps most exciting among these are in bioinformatics as AI allows for new and increasingly powerful ways of understanding genomics, p...
Vaccine Design by Reverse Vaccinology and Machine Learning.
Methods in molecular biology (Clifton, N.J.)
Jan 1, 2022
Reverse vaccinology (RV) is the state-of-the-art vaccine development strategy that starts with predicting vaccine antigens by bioinformatics analysis of the whole genome of a pathogen of interest. Vaxign is the first web-based RV vaccine prediction m...
Vaxign2: the second generation of the first Web-based vaccine design program using reverse vaccinology and machine learning.
Nucleic acids research
Jul 2, 2021
Vaccination is one of the most significant inventions in medicine. Reverse vaccinology (RV) is a state-of-the-art technique to predict vaccine candidates from pathogen's genome(s). To promote vaccine development, we updated Vaxign2, the first web-bas...
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