AIMC Topic: Vaccines

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Enhancing Vaccine Safety Surveillance: Extracting Vaccine Mentions from Emergency Department Triage Notes Using Fine-Tuned Large Language Models.

Studies in health technology and informatics
This study evaluates fine-tuned Llama 3.2 models for extracting vaccine-related information from emergency department triage notes to support near real-time vaccine safety surveillance. Prompt engineering was used to initially create a labeled datase...

Unveiling differential adverse event profiles in vaccines via LLM text embeddings and ontology semantic analysis.

Journal of biomedical semantics
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...

Vaxi-DL: An Artificial Intelligence-Enabled Platform for Vaccine Development.

Methods in molecular biology (Clifton, N.J.)
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
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
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.)
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.)
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
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...

Artificial intelligence and the hunt for immunological disorders.

Current opinion in allergy and clinical immunology
PURPOSE OF REVIEW: Artificial intelligence has pervasively transformed many industries and is beginning to shape medical practice. New use cases are being identified in subspecialty domains of medicine and, in particular, application of artificial in...