Large language models to process, analyze, and synthesize biomedical texts: a scoping review

Large language models to process, analyze, and synthesize biomedical texts: a scoping review

Abstract The advent of large language models (LLMs) such as BERT and, more recently, GPT, is transforming our approach of analyzing and understanding biomedical texts. To stay informed about the latest advancements in this area, there is a need for up-to-date summaries on the role of LLM in Natural...

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Bibliographic Details
Main Authors: Simona Emilova Doneva, Sijing Qin, Beate Sick, Tilia Ellendorff, Jean-Philippe Goldman, Gerold Schneider, Benjamin Victor Ineichen
Format: Article
Language:English
Published: Springer 2024-12-01
Series:Discover Artificial Intelligence
Subjects:
Natural language processing
Bioinformatics
Biomedicine
Large language models
BERT
Evidence synthesis
Online Access:https://doi.org/10.1007/s44163-024-00197-2
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https://doi.org/10.1007/s44163-024-00197-2

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