A multi-center distributed learning approach for Parkinson's disease classification using the traveling model paradigm

A multi-center distributed learning approach for Parkinson's disease classification using the traveling model paradigm

Distributed learning is a promising alternative to central learning for machine learning (ML) model training, overcoming data-sharing problems in healthcare. Previous studies exploring federated learning (FL) or the traveling model (TM) setup for medical image-based disease classification often reli...

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Bibliographic Details
Main Authors: Raissa Souza, Emma A. M. Stanley, Milton Camacho, Richard Camicioli, Oury Monchi, Zahinoor Ismail, Matthias Wilms, Nils D. Forkert
Format: Article
Language:English
Published: Frontiers Media S.A. 2024-02-01
Series:Frontiers in Artificial Intelligence
Subjects:
traveling model
federated learning
distributed learning
Parkinson's disease
multi-center
Online Access:https://www.frontiersin.org/articles/10.3389/frai.2024.1301997/full

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https://www.frontiersin.org/articles/10.3389/frai.2024.1301997/full

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