Multimodal prediction of metastatic relapse using federated deep learning in soft-tissue sarcoma with a complex genomic profile

Abstract Soft Tissue sarcomas (STS) are a group of heterogeneous and complex diseases where being able to predict the appearance of metastases is key to inform clinical decisions, especially the prescription of adjuvant chemotherapy. We developed SarcNet: a multimodal deep-learning algorithm based o...

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Ngā kaituhi matua:	Charles Maussion, Jean-Michel Coindre, Jean-Yves Blay, Kathryn Schutte, Axel Camara, François Le Loarer, Raul Perret, Myriam Jean-Denis, Alexandra Meurgey, Françoise Ducimetiere, Antoine Giraud, Jean-Baptiste Courrèges, Pierre Meeus, Audrey Michot, Etienne Bendjebbar, Jean Ogier du Terrail, Antoine Italiano, Marie Karanian
Hōputu:	Artigo
Reo:	Inglês
I whakaputaina:	Nature Portfolio 2025-10-01
Rangatū:	Scientific Reports
Urunga tuihono:	https://doi.org/10.1038/s41598-025-20495-8
Ngā Tūtohu:	Tāpirihia he Tūtohu Kāore He Tūtohu, Me noho koe te mea tuatahi ki te tūtohu i tēnei pūkete!

Multimodal prediction of metastatic relapse using federated deep learning in soft-tissue sarcoma with a complex genomic profile

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