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

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Federated learning for predicting histological response to neoadjuvant chemotherapy in triple-negative breast cancer - Nature Medicine
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FederatedLearning improves prediction of the histological response to Neoadjuvant Chemotherapy in patients with triple-negative BreastCancer, showing the feasibility of this approach for analysis of multi-center cohorts of patients with rare diseases.

Fig. 2: Univariate and multivariate associations between diagnosis variables and NACT histological response.

Fig. 3: Performance comparison between local and collaborative FL training on clinical or WSI data to predict treatment response in TNBC. Fig. 4: Performance of WSI-based methods versus the best models using clinical data on the separate test.Data underpinning this study are under restricted access and are not freely available as they contain patients’ data, and specific clearance from the ethics committee is required in each center. Data can, however, be made available upon reasonable request from Centre Léon Bérard, Institut Curie, Institut Gustave Roussy and Institut Universitaire du Cancer Toulouse Oncopole.

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