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Benchmarking Collaborative Learning Methods Cost-Effectiveness for
  Prostate Segmentation

Benchmarking Collaborative Learning Methods Cost-Effectiveness for Prostate Segmentation

29 September 2023
Lucia Innocenti
Michela Antonelli
Francesco Cremonesi
Kenaan Sarhan
Alejandro Granados
Vicky Goh
Sebastien Ourselin
Marco Lorenzi
    FedML
ArXivPDFHTML

Papers citing "Benchmarking Collaborative Learning Methods Cost-Effectiveness for Prostate Segmentation"

4 / 4 papers shown
Title
A cautionary tale on the cost-effectiveness of collaborative AI in
  real-world medical applications
A cautionary tale on the cost-effectiveness of collaborative AI in real-world medical applications
Francesco Cremonesi
Lucia Innocenti
Sebastien Ourselin
Vicky Goh
Michela Antonelli
Marco Lorenzi
FedML
99
0
0
09 Dec 2024
Enhancing Privacy in Federated Learning: Secure Aggregation for
  Real-World Healthcare Applications
Enhancing Privacy in Federated Learning: Secure Aggregation for Real-World Healthcare Applications
Riccardo Taiello
Sergen Cansiz
Marc Vesin
Francesco Cremonesi
Lucia Innocenti
Melek Önen
Marco Lorenzi
43
0
0
02 Sep 2024
The Future of Digital Health with Federated Learning
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
1,690
0
18 Mar 2020
Dropout as a Bayesian Approximation: Representing Model Uncertainty in
  Deep Learning
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
Y. Gal
Zoubin Ghahramani
UQCV
BDL
247
9,042
0
06 Jun 2015
1