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Study of the performance and scalability of federated learning for
  medical imaging with intermittent clients

Study of the performance and scalability of federated learning for medical imaging with intermittent clients

18 July 2022
Judith Sáinz-Pardo Díaz
Á. García
    FedML
    OOD
ArXivPDFHTML

Papers citing "Study of the performance and scalability of federated learning for medical imaging with intermittent clients"

9 / 9 papers shown
Title
Enhancing the Convergence of Federated Learning Aggregation Strategies with Limited Data
Judith Sáinz-Pardo Díaz
Á. García
36
0
0
28 Jan 2025
Federated and Transfer Learning for Cancer Detection Based on Image
  Analysis
Federated and Transfer Learning for Cancer Detection Based on Image Analysis
Amine Bechar
Y. Elmir
Yassine Himeur
Rafik Medjoudj
Abbes Amira
MedIm
38
4
0
30 May 2024
PAFedFV: Personalized and Asynchronous Federated Learning for Finger
  Vein Recognition
PAFedFV: Personalized and Asynchronous Federated Learning for Finger Vein Recognition
Hengyu Mu
Jian Guo
Chong Han
Lijuan Sun
FedML
24
5
0
20 Apr 2024
Multimodal Federated Learning in Healthcare: a Review
Multimodal Federated Learning in Healthcare: a Review
Jacob Thrasher
Alina Devkota
Prasiddha Siwakotai
Rohit Chivukula
Pranav Poudel
Chaunbo Hu
Binod Bhattarai
P. Gyawali
30
7
0
14 Oct 2023
Federated Learning: A Cutting-Edge Survey of the Latest Advancements and
  Applications
Federated Learning: A Cutting-Edge Survey of the Latest Advancements and Applications
Azim Akhtarshenas
Mohammad Ali Vahedifar
Navid Ayoobi
B. Maham
Tohid Alizadeh
Sina Ebrahimi
David López-Pérez
FedML
28
5
0
08 Oct 2023
Comparison of machine learning models applied on anonymized data with
  different techniques
Comparison of machine learning models applied on anonymized data with different techniques
Judith Sáinz-Pardo Díaz
Á. García
14
5
0
12 May 2023
Federated Learning for Medical Applications: A Taxonomy, Current Trends,
  Challenges, and Future Research Directions
Federated Learning for Medical Applications: A Taxonomy, Current Trends, Challenges, and Future Research Directions
A. Rauniyar
D. Hagos
Debesh Jha
J. E. Haakegaard
Ulas Bagci
D. Rawat
Vladimir Vlassov
OOD
43
90
0
05 Aug 2022
FedML: A Research Library and Benchmark for Federated Machine Learning
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
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
1,707
0
18 Mar 2020
1