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Distributed learning: a reliable privacy-preserving strategy to change multicenter collaborations using AI
45
Zitationen
10
Autoren
2021
Jahr
Abstract
Distributed learning resulted in a reliable strategy for model development; indeed, it performed equally to models trained on centralized datasets. Sensitive data can get preserved since they are not shared for model development. Distributed learning constitutes a promising solution for ML-based research and practice since large, diverse datasets are crucial for success.
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