ArticleJournal of imaging informatics in medicine2026
Multicohort Evaluation of Acquisition Confounding in Single-Site Lung-CT Malignancy Classification with Frozen Foundation-Model Features.
Article in Journal of imaging informatics in medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Frozen foundation-model features are promoted as an annotation-sparing route to medical-image classification, yet whether their performance reflects diagnostic signal or site-specific shortcuts is rarely tested. On a single-site hospital cohort (187 cancer and 194 benign scans, 303 patients), frozen Models-Genesis whole-scan features classified cancer versus benign at an out-of-fold AUC of 0.994 under patient-grouped cross-validation and transferred near chance to two external cohorts. One is LIDC-IDRI, where malignancy is a median radiologist rating, not a confirmed diagnosis. The other carries confirmed diagnoses matching the development endpoint. We tested acquisition as a competing explanation. The two classes had been reconstructed under different protocols (0.7 mm versus 1.0 mm slice spacing), and a classifier reading six acquisition header fields, and no image data, reached 0.996, within 0.001 of the frozen-feature result (
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