Back to search

Article

Vision-Language Foundation Models Do Not Transfer to Medical Imaging Classification: A Negative Result on Chest X-ray Diagnosis

2025-12-08

Abstract excerpt

Vision-language models (VLMs) pretrained on web-scale data have achieved remarkable performance across diverse tasks, leading to widespread adoption in industry. A natural question is whether these powerful representations transfer to specialized medical imaging domains, and whether domain-specific medical pretraining improves transfer. We tested these hypotheses using two VLMs on the NIH ChestX-ray14 benchmark: Q...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work
a8fff097-6a15-58bb-87bc-ac57326d9bf1
DOI
10.64898/2025.12.06.25341759
Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest
Interactive article relationship graphSelect a related publication card to move it into the centre and load its closest explainable connections. Solid lines are source-backed structured connections. Dashed lines are semantic discovery signals and are not scientific evidence.
Vision-Language Foundation Models Do Not Transfer to Medical Imaging Classification: A Negative Result on Chest X-ray DiagnosisDOI 10.64898/2025.12.06.25341759
Select a neighboring publication to make it the new centre.