End-to-end prediction of clinical outcomes in head and neck squamous cell carcinoma with foundation model-based multiple instance learning

Authors

Keno K. Bressem (ORCID: https://orcid.org/0000-0001-9249-8624)
Daniel Truhn (ORCID: https://orcid.org/0000-0002-9605-0728)
Raquel Pérez-López (ORCID: https://orcid.org/0000-0002-9176-0130)
Alexander T. Pearson (ORCID: https://orcid.org/0000-0003-2801-7456)
Asier Rabasco Meneghetti (ORCID: https://orcid.org/0000-0002-1508-9410)
Marta Ligero (ORCID: https://orcid.org/0000-0001-9824-7316)
Steffen Löck (ORCID: https://orcid.org/0000-0002-7017-3738)
Jens‐Peter Kühn (ORCID: https://orcid.org/0000-0003-3258-930X)
Zunamys I. Carrero (ORCID: https://orcid.org/0000-0001-8501-1566)
Titus Josef Brinker (ORCID: https://orcid.org/0000-0002-3620-5919)
Sven Nebelung (ORCID: https://orcid.org/0000-0002-5267-9962)
Jakob Nikolas Kather

Institutions

German Cancer Research Center (DE)
Heidelberg University (DE)
Helmholtz-Zentrum Dresden-Rossendorf (DE)
University Hospital Heidelberg (DE)
University of Chicago (US)
National Center for Tumor Diseases (DE)
Vall d'Hebron Hospital Universitari (ES)
OncoRay (DE)
University Hospital Carl Gustav Carus (DE)
Vall d'Hebron Institute of Oncology (ES)
Technische Universität Dresden (DE)

Publication Details

Journal: BMC Artificial Intelligence
Published: 2025-06-24
DOI: https://doi.org/10.1186/s44398-025-00003-8
Citations: 3
Primary Topic: AI in cancer detection
Type: article
Field-Weighted Citation Impact: 7.44

Funders

National Institute for Health and Care Research
Deutsche Forschungsgemeinschaft
Bundesministerium für Bildung und Forschung
Technische Universität Dresden
Deutsche Krebshilfe
National Institutes of Health
HORIZON EUROPE European Research Council

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article

End-to-end prediction of clinical outcomes in head and neck squamous cell carcinoma with foundation model-based multiple instance learning

Keno K. Bressem, Daniel Truhn, Raquel Pérez-López, Alexander T. Pearson et al.

Jun 24, 2025

3 citations

BMC Artificial Intelligence

AI in cancer detection

7.44

article

End-to-end prediction of clinical outcomes in head and neck squamous cell carcinoma with foundation model-based multiple instance learning

Keno K. Bressem, Daniel Truhn, Raquel Pérez-López, Alexander T. Pearson, Asier Rabasco Meneghetti, Marta Ligero, Steffen Löck, Jens‐Peter Kühn, Zunamys I. Carrero, Titus Josef Brinker, Sven Nebelung, Jakob Nikolas Kather

June 24, 2025article en

3 citations

Abstract

No abstract available for this paper.

BMC Artificial IntelligenceVol. 1(1)

German Cancer Research Center (DE), Heidelberg University (DE), Helmholtz-Zentrum Dresden-Rossendorf (DE), University Hospital Heidelberg (DE), University of Chicago (US), National Center for Tumor Diseases (DE), Vall d'Hebron Hospital Universitari (ES), OncoRay (DE), University Hospital Carl Gustav Carus (DE), Vall d'Hebron Institute of Oncology (ES), Technische Universität Dresden (DE)

National Institute for Health and Care Research, Deutsche Forschungsgemeinschaft, Bundesministerium für Bildung und Forschung, Technische Universität Dresden, Deutsche Krebshilfe, National Institutes of Health, HORIZON EUROPE European Research Council

Openalex Percentile: Top 3%

AI in cancer detection

7.44

DOI Open Access PDF OpenAlex

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