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A multi-center study on the adaptability of a shared foundation model for electronic health records
42
Zitationen
9
Autoren
2024
Jahr
Abstract
required fewer than 1% of training examples to match the fully trained GBM's performance, and was 60 to 90% more sample-efficient than training local foundation models from scratch. Our findings demonstrate that adapting EHR foundation models across hospitals provides improved prediction performance at less cost, underscoring the utility of base foundation models as modular components to streamline the development of healthcare AI.
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