Federated learning for predicting histological response to neoadjuvant chemotherapy in triple-negative breast cancer

Jean Ogier du Terrail; Armand Léopold; Clément Joly; Constance Béguier; Mathieu Andreux; Charles Maussion; Benoît Schmauch; Eric W. Tramel; Etienne Bendjebbar; Mikhail Zaslavskiy; Gilles Wainrib; Maud Milder; Julie Gervasoni; Julien Guérin; Thierry Durand; Alain Livartowski; Kelvin Moutet; Clément Gautier; Inal Djafar; Anne-Laure Moisson; Camille Marini; Mathieu Galtier; Félix Balazard; Rémy Dubois; Jeverson Moreira; Antoine Simon; Damien Drubay; Magali Lacroix‐Triki; Camille Franchet; Guillaume Bataillon; Pierre-Étienne Heudel

doi:10.1038/s41591-022-02155-w

JOURNAL ARTICLE

Federated learning for predicting histological response to neoadjuvant chemotherapy in triple-negative breast cancer

Jean Ogier du Terrail Armand Léopold Clément Joly Constance Béguier Mathieu Andreux Charles Maussion Benoît Schmauch Eric W. Tramel Etienne Bendjebbar Mikhail Zaslavskiy Gilles Wainrib Maud Milder Julie Gervasoni Julien Guérin Thierry Durand Alain Livartowski Kelvin Moutet Clément Gautier Inal Djafar Anne-Laure Moisson Camille Marini Mathieu Galtier Félix Balazard Rémy Dubois Jeverson Moreira Antoine Simon Damien Drubay Magali Lacroix‐Triki Camille Franchet Guillaume Bataillon Pierre-Étienne Heudel

Year: 2023 Journal: Nature Medicine Vol: 29 (1)Pages: 135-146 Publisher: Nature Portfolio

DOI: 10.1038/s41591-022-02155-w

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Keywords:

Triple-negative breast cancer Breast cancer Medicine Biomarker Chemotherapy Triple negative Cancer Oncology Internal medicine Machine learning Computer science

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Topics

AI in cancer detection

Physical Sciences → Computer Science → Artificial Intelligence

Breast Cancer Treatment Studies

Life Sciences → Biochemistry, Genetics and Molecular Biology → Cancer Research

Breast Lesions and Carcinomas

Health Sciences → Medicine → Pathology and Forensic Medicine

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