From Embeddings to Accuracy: Comparing Foundation Models for Radiographic Classification.

Foundation models, pre-trained on extensive datasets, have significantly advanced machine learning by providing robust and transferable embeddings applicable to various domains, including medical imaging diagnostics. This study evaluates the utility of embeddings derived from both general-purpose an...

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Bibliographic Details

Published in:	Journal of Imaging Informatics in Medicine Vol. 39; no. 4; pp. 3196 - 3208
Main Authors:	Li, Xue, Merkow, Jameson, Codella, Noel C. F., Santamaria-Pang, Alberto, Sangani, Naiteek, Ersoy, Alexander, Burt, Christopher, Garrett, John W., Bruce, Richard J., Warner, Joshua D., Bradshaw, Tyler, Tarapov, Ivan, Lungren, Matthew P., McMillan, Alan B.
Format:	diagnostic images research tables/charts Journal Article
Published:	Springer Nature Aug2026
Online Access:	View this record in EBSCOhost