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Topic Modeling

Adapted large language models can outperform medical experts in clinical text summarization

Dave Van Veen, Cara Van Uden, Louis Blankemeier, Jean-Benoit Delbrouck, Asad Aali, Christian Bluethgen, Anuj Pareek, Malgorzata Polacin, Eduardo Pontes Reis, Anna Seehofnerová, Nidhi Rohatgi, Poonam Hosamani, William Collins, Neera Ahuja, Curtis P. Langlotz, Jason Hom, Sergios Gatidis, John M. Pauly, Akshay Chaudhari

Topic ModelingBiomedical Text Mining and OntologiesMachine Learning in Healthcare
Published February 27, 2024Read PDF ↗View on arXiv ↗

Abstract

Sourced from arXiv · Updated September 2, 2026

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What is "Adapted large language models can outperform medical experts in clinical text summarization" about?

Adapted large language models can outperform medical experts in clinical text summarization

Who wrote this paper?

Dave Van Veen, Cara Van Uden, Louis Blankemeier, Jean-Benoit Delbrouck, Asad Aali, Christian Bluethgen, Anuj Pareek, Malgorzata Polacin, Eduardo Pontes Reis, Anna Seehofnerová, Nidhi Rohatgi, Poonam Hosamani, William Collins, Neera Ahuja, Curtis P. Langlotz, Jason Hom, Sergios Gatidis, John M. Pauly, Akshay Chaudhari

Where can I read the full paper?

The full text is available as a PDF on arXiv (linked above), published February 27, 2024.

Does this paper have a DOI?

Yes: https://doi.org/10.1038/s41591-024-02855-5.