Abstract 1939: Multimodal prediction of metastatic relapse using federated deep learning outperforms state-of-the-art methods in soft-tissue sarcoma

• Published in: Cancer research (Chicago, Ill.) Vol. 82; no. 12_Supplement; p. 1939
• Main Authors: Maussion, Charles, Coindre, Jean-Michel, Blay, Jean-Yves, Schutte, Kathryn, Camara, Axel, Loarer, François Le, Perret, Raul, Jean-Denis, Myriam, Meurgey, Alexandra, Ducimetiere, Françoise, Giraud, Antoine, Courrèges, Jean-Baptiste, Gautier, Clément, Bendjebbar, Etienne, Terrail, Jean Du, Italiano, Antoine, Karanian, Marie
• Format: Journal Article
• Language: English
• Published: 15.06.2022

Abstract Soft Tissue sarcomas (STS) are a group of heterogeneous and complex diseases. Being able to predict the appearance of metastases is key to inform clinical decisions, especially the prescription of perioperative chemotherapy. While multiple methods including multivariable nomograms have been...