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Centralized pooling and federated learning for Canadian patient-level data sharing in multicenter medical AI: A scoping review
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DOI：10.1016/j.artmed.2026.103422.png)
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Abstract
En 中文
• First national analysis of patient-level data sharing in Canadian medical AI. • Centralized pooling used in 95% of multicenter collaborations. • Decentralized or federated methods reported in only 5% of studies. • 80% of multicenter studies involve international data partnerships. • Only one decentralized collaboration operated entirely within Canada.
Keywords:
patient-level data sharing
federated learning
multicenter collaborations
medical AI
centralized pooling
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