This paper is in the following e-collection/theme issue:

Theme Issue 2025: Artificial Intelligence in Oncology (5) AI applications in genomics and pathology informatics, including ‘Generative AI’ (16) Cancer Prognosis Models and Machine Learning (46) Clinical Cancer Research (106) Artificial Intelligence (1958) Applications of AI (229) Tools, Programs and Algorithms (351)

Published on in Vol 6 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/70706, first published .
Extracting Knowledge From Scientific Texts on Patient-Derived Cancer Models Using Large Language Models: Algorithm Development and Validation Study

Extracting Knowledge From Scientific Texts on Patient-Derived Cancer Models Using Large Language Models: Algorithm Development and Validation Study

Extracting Knowledge From Scientific Texts on Patient-Derived Cancer Models Using Large Language Models: Algorithm Development and Validation Study

Authors of this article:

Jiarui Yao1, 2 Author Orcid Image ;   Zinaida Perova3 Author Orcid Image ;   Tushar Mandloi3 Author Orcid Image ;   Elizabeth Lewis3 Author Orcid Image ;   Helen Parkinson3 Author Orcid Image ;   Guergana Savova1, 2 Author Orcid Image
Article Authors Cited by Tweetations Metrics

Jiarui Yao   1, 2 * , PhD ;   Zinaida Perova   3 * , PhD ;   Tushar Mandloi   3 , MSc ;   Elizabeth Lewis   3 , MSc ;   Helen Parkinson   3 , PhD ;   Guergana Savova   1, 2 , PhD

1 Computational Health Informatics Program, Boston Children's Hospital, Boston, MA, United States

2 Harvard Medical School, Boston, MA, United States

3 European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, United Kingdom

*these authors contributed equally

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