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  5. Large language models for science and medicine

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Article
en
2024

Large language models for science and medicine

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0 Files

en
2024
Vol 54 (6)
Vol. 54
DOI: 10.1111/eci.14183

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John P A Ioannidis
John P A Ioannidis

Stanford University

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Amalio Telenti
Michael Auli
Brian Hie
+3 more

Abstract

Abstract Large language models (LLMs) are a type of machine learning model that learn statistical patterns over text, such as predicting the next words in a sequence of text. Both general purpose and task‐specific LLMs have demonstrated potential across diverse applications. Science and medicine have many data types that are highly suitable for LLMs, such as scientific texts (publications, patents and textbooks), electronic medical records, large databases of DNA and protein sequences and chemical compounds. Carefully validated systems that can understand and reason across all these modalities may maximize benefits. Despite the inevitable limitations and caveats of any new technology and some uncertainties specific to LLMs, LLMs have the potential to be transformative in science and medicine.

How to cite this publication

Amalio Telenti, Michael Auli, Brian Hie, M. Cyrus Maher, Suchi Saria, John P A Ioannidis (2024). Large language models for science and medicine. , 54(6), DOI: https://doi.org/10.1111/eci.14183.

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Publication Details

Type

Article

Year

2024

Authors

6

Datasets

0

Total Files

0

Language

en

DOI

https://doi.org/10.1111/eci.14183

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