Federated learning enables big data for rare cancer boundary detection

Federated learning enables big data for rare cancer boundary detection

Hiển thị phiên bản (1) khác

Although machine learning (ML) has shown promise across disciplines, out-of-sample generalizability is concerning. This is currently addressed by sharing multi-site data, but such centralization is challenging/infeasible to scale due to various limitations. Federated ML (FL) provides an alternative...

Mô tả đầy đủ

Chi tiết về thư mục
Những tác giả chính: Pati, S, Baid, U, Edwards, B, Sheller, M, Wang, S-H, Reina, GA, Foley, P, Gruzdev, A, Karkada, D, Davatzikos, C, Sako, C, Ghodasara, S, Bilello, M, Mohan, S, Vollmuth, P, Brugnara, G, Preetha, CJ, Sahm, F, Maier-Hein, K, Zenk, M, Bendszus, M, Wick, W, Calabrese, E, Rudie, J, Villanueva-Meyer, J, Cha, S, Ingalhalikar, M, Jadhav, M, Pandey, U, Saini, J, Garrett, J, Larson, M, Jeraj, R, Currie, S, Frood, R, Fatania, K, Huang, RY, Chang, K, Balaña, C, Capellades, J, Puig, J, Trenkler, J, Pichler, J, Necker, G, Haunschmidt, A, Meckel, S, Shukla, G, Liem, S, Alexander, GS, Lombardo, J, Kamnitsas, K
Định dạng: Journal article
Ngôn ngữ:English
Được phát hành: Springer Nature 2022

Những quyển sách tương tự