ESMO guidance on the use of Large Language Models in Clinical Practice (ELCAP)

ELCAP provides a three-tier framework and basic practical guidance for LLM use in oncology. ESMO supports efforts to use this framework to improve patient care, but warns against unsupervised or unvalidated use.

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Publication Details

Journal
Annals of Oncology
Published
2025-10-18
DOI
https://doi.org/10.1016/j.annonc.2025.09.001
Citations
5
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
3.27

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article

ESMO guidance on the use of Large Language Models in Clinical Practice (ELCAP)

Alice Indini, George E. Pentheroudakis, Emanuela Romano, Isabella C. Wiest et al.
5 citations
Annals of Oncology
Artificial Intelligence in Healthcare and Education
3.27
article

ESMO guidance on the use of Large Language Models in Clinical Practice (ELCAP)

Alice Indini, George E. Pentheroudakis, Emanuela Romano, Isabella C. Wiest, Nadia Harbeck, Susan Halabi, Maria Alice Franzoi, Mihaela D. Aldea, Evelyn Yi Ting Wong, Antonios Valachis, Loïc Verlingue, Stephen Gilbert, Renato Umeton, Yongjie Yang, Iain Tan, M. Koopman, Elizabeth Smyth, Arsela Prelaj, Jakob Nikolas Kather, J.-F. Vibert, George Kapetanakis
article en
5 citations

Abstract

ELCAP provides a three-tier framework and basic practical guidance for LLM use in oncology. ESMO supports efforts to use this framework to improve patient care, but warns against unsupervised or unvalidated use.

Annals of OncologyVol. 36(12)
St. Jude Children's Research Hospital (US), Inserm (FR), National Health Research Institutes (TW), Duke University (US), Utrecht University (NL), Cornell University (US), Heidelberg University (DE), Örebro University (SE), Université Paris-Saclay (FR), European Society for Medical Oncology (CH), Institut Gustave Roussy (FR), University Hospital Heidelberg (DE), University Medical Center Utrecht (NL), Centre Léon Bérard (FR), National Center for Tumor Diseases (DE), Breast Center (CH), Hellenic Cancer Society (GR), Duke Medical Center (US), Else Kröner-Fresenius-Stiftung (DE), National Cancer Centre Singapore (SG), Oxford Applied Research (United Kingdom) (GB), Oxford BioMedica (United Kingdom) (GB), Science Oxford (GB), Duke University Hospital (US), Fondazione IRCCS Istituto Nazionale dei Tumori (IT), University Hospital Carl Gustav Carus (DE), Massachusetts Institute of Technology (US), Institut Curie (FR), Ludwig-Maximilians-Universität München (DE)
Conquer Cancer Foundation, Breast Cancer Research Foundation, Amgen, Bristol-Myers Squibb, Eli Lilly and Company, Pfizer, AstraZeneca, Gilead Sciences, Taiho Pharmaceutical, Les Laboratories Pierre Fabre, BeiGene, Seagen, Natera, Agence Nationale de la Recherche, European Society for Medical Oncology, Servier, Ipsen, Daiichi Sankyo Europe
Openalex Percentile: Top 7%
Artificial Intelligence in Healthcare and Education
3.27
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