Federating Medical Deep Learning Models from Private Jupyter Notebooks to Distributed Institutions

Federating Medical Deep Learning Models from Private Jupyter Notebooks to Distributed Institutions

Deep learning-based algorithms have led to tremendous progress over the last years, but they face a bottleneck as their optimal development highly relies on access to large datasets. To mitigate this limitation, cross-silo federated learning has emerged as a way to train collaborative models among m...

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Bibliographic Details
Main Authors: Laëtitia Launet, Yuandou Wang, Adrián Colomer, Jorge Igual, Cristian Pulgarín-Ospina, Spiros Koulouzis, Riccardo Bianchi, Andrés Mosquera-Zamudio, Carlos Monteagudo, Valery Naranjo, Zhiming Zhao
Format: Article
Language:English
Published: MDPI AG 2023-01-01
Series:Applied Sciences
Subjects:
federated learning
Jupyter notebook
medical image analysis
collaborative models
cloud environment
distributed medical applications
Online Access:https://www.mdpi.com/2076-3417/13/2/919

Internet

https://www.mdpi.com/2076-3417/13/2/919

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