CPC with full fine-tuning yields a small but significant AUROC gain over target-only training at 5% target data in one of two tasks, and temporal patterns transfer better than point-of-care decisions.
Reproducibility in machine learning for health research: Still a ways to go
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Contrastive Representation Learning Helps Cross-institutional Knowledge Transfer: A Study in Pediatric Ventilation Management
CPC with full fine-tuning yields a small but significant AUROC gain over target-only training at 5% target data in one of two tasks, and temporal patterns transfer better than point-of-care decisions.