A Strong Baseline for Domain Adaptation and Generalization in Medical Imaging

Yao, Li, Prosky, Jordan, Covington, Ben, Lyman, Kevin

arXiv.org Artificial Intelligence 

This work provides a strong baseline for the problem of multi-source multi-target domain adaptation and generalization in medical imaging. Using a diverse collection of ten chest X-ray datasets, we empirically demonstrate the benefits of training medical imaging deep learning models on varied patient populations for generalization to out-of-sample domains.

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