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

Reviews on Innovations in Cancer (106) Natural Language Processing (1224) Decision Support for Health Professionals (2114) Electronic Health Records (1655) Chatbots and Conversational Agents (1131) Artificial Intelligence (4527) Generative Language Models Including ChatGPT (1406)

Published on in Vol 11 (2025)

This is a member publication of University of Toronto

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/65984, first published .
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Large Language Model Applications for Health Information Extraction in Oncology: Scoping Review

Large Language Model Applications for Health Information Extraction in Oncology: Scoping Review

Authors of this article:

David Chen1 Author Orcid Image ;   Saif Addeen Alnassar2 Author Orcid Image ;   Kate Elizabeth Avison2 Author Orcid Image ;   Ryan S Huang1 Author Orcid Image ;   Srinivas Raman3 Author Orcid Image
Article Authors Cited by (33) Tweetations Metrics

Journals

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  13. Loaiza-Bonilla A, Thaker N, Tuysuz E, Yerdan S, Kurnaz S. Evaluating Multimodal LLMs for Information Extraction from Oncology Reports Requires a Clinically Curated Ground Truth—Two-Phase Evaluation of GPT-4.1 versus GPT-4.0. AI in Precision Oncology 2026;3(1):14 View
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  15. Xu K, Xu Y, Shi Q. Harnessing computational power for intelligent oncology in the age of large models: Status, challenges, and prospects. Intelligent Oncology 2026;2(1):100038 View
  16. Wang Y, Wang Q, Xun Y, Zhou Q, Zhang H, Liu H, Qin Y, Wu M, Wang Z, Li H, Estill J, Chen Y. Managing Conflict of Interest in Clinical Practice Guidelines With Artificial Intelligence: Insights From Large Language Models and Beyond. Journal of Evidence-Based Medicine 2026;19(1) View
  17. Wells C, Han A, Joseph N, Varghese C, O’Grady G, Bissett I. Learning from complaints about surgical care: a large language model-assisted sequential methods analysis. BMJ Quality & Safety 2026:bmjqs-2025-019556 View
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Conference Proceedings

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