Year: 2019
Type: preprint
Abstract: 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.
Source: arXiv (Cornell University)
Authors: Yao, Li, Prosky, Jordan, Covington, Ben, Lyman, Kevin
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W2933063649