Journal article
Application of large language models in medicine
- Abstract:
- Large language models (LLMs), such as ChatGPT, have received great attention owing to their capabilities for understanding and generating human language. Despite a trend in researching the application of LLMs in supporting different medical tasks (such as enhancing clinical diagnostics and providing medical education), a comprehensive assessment of their development, practical applications and outcomes in the medical space is still missing. Therefore, this Review aims to provide an overview of the development and deployment of LLMs in medicine, including the challenges and opportunities they face. In terms of development, we discuss the principles of existing medical LLMs, including their basic model structures, number of parameters, and sources and scales of data used for model development. In terms of deployment, we compare different LLMs across various medical tasks and with state-of-the-art lightweight models.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
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- Files:
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(Preview, Accepted manuscript, pdf, 2.0MB, Terms of use)
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- Publisher copy:
- 10.1038/s44222-025-00279-5
Authors
+ Innovation and Technology Commission
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- Funder identifier:
- https://ror.org/04vf9tr09
- Programme:
- Hong Kong Center for Cerebro-cardiovascular Health Engineering (COCHE)
+ Engineering and Physical Sciences Research Council
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- Funder identifier:
- https://ror.org/0439y7842
- Publisher:
- Springer Nature
- Journal:
- Nature Reviews Bioengineering More from this journal
- Volume:
- 3
- Issue:
- 6
- Pages:
- 445-464
- Publication date:
- 2025-04-07
- Acceptance date:
- 2025-01-20
- DOI:
- EISSN:
-
731-6092
- Language:
-
English
- Pubs id:
-
2085045
- Local pid:
-
pubs:2085045
- Deposit date:
-
2025-02-11
- ARK identifier:
Terms of use
- Copyright holder:
- Springer Nature Limited
- Copyright date:
- 2025
- Rights statement:
- © Springer Nature Limited 2025.
- Notes:
- The author accepted manuscript (AAM) of this paper has been made available under the University of Oxford's Open Access Publications Policy, and a CC BY public copyright licence has been applied.
- Licence:
- CC Attribution (CC BY)
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