AI RESEARCH
A Reasoning-Enabled Vision-Language Foundation Model for Chest X-ray Interpretation
arXiv CS.AI
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ArXi:2604.00493v1 Announce Type: cross Chest X-rays (CXRs) are among the most frequently performed imaging examinations worldwide, yet rising imaging volumes increase radiologist workload and the risk of diagnostic errors. Although artificial intelligence (AI) systems have shown promise for CXR interpretation, most generate only final predictions, without making explicit how visual evidence is translated into radiographic findings and diagnostic predictions. We present CheXOne, a reasoning-enabled vision-language model for CXR interpretation.