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2304.12012
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Fed-BioMed: Open, Transparent and Trusted Federated Learning for Real-world Healthcare Applications
24 April 2023
Francesco Cremonesi
Marc Vesin
Sergen Cansiz
Yannick Bouillard
Irene Balelli
Lucia Innocenti
Santiago Silva
Samy Ayed
Riccardo Taiello
Laetita Kameni
Richard Vidal
Fanny Orlhac
C. Nioche
Nathan Lapel
B. Houis
R. Modzelewski
O. Humbert
Melek Önen
Marco Lorenzi
FedML
OOD
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Papers citing
"Fed-BioMed: Open, Transparent and Trusted Federated Learning for Real-world Healthcare Applications"
4 / 4 papers shown
Title
Federated and Transfer Learning for Cancer Detection Based on Image Analysis
Amine Bechar
Y. Elmir
Yassine Himeur
Rafik Medjoudj
Abbes Amira
MedIm
41
4
0
30 May 2024
FedML: A Research Library and Benchmark for Federated Machine Learning
Chaoyang He
Songze Li
Jinhyun So
Xiao Zeng
Mi Zhang
...
Yang Liu
Ramesh Raskar
Qiang Yang
M. Annavaram
Salman Avestimehr
FedML
168
564
0
27 Jul 2020
IBM Federated Learning: an Enterprise Framework White Paper V0.1
Heiko Ludwig
Nathalie Baracaldo
Gegi Thomas
Yi Zhou
Ali Anwar
...
Sean Laguna
Mikhail Yurochkin
Mayank Agarwal
Ebube Chuba
Annie Abay
FedML
131
157
0
22 Jul 2020
The Future of Digital Health with Federated Learning
Nicola Rieke
Jonny Hancox
Wenqi Li
Fausto Milletari
H. Roth
...
Ronald M. Summers
Andrew Trask
Daguang Xu
Maximilian Baust
M. Jorge Cardoso
OOD
174
1,707
0
18 Mar 2020
1
