Decoupling Visual Parsing and Diagnostic Reasoning for Vision-Language Models (GPT-4o and GPT-5): Analysis Using Thoracic Imaging Quiz Cases

Background: Vision-language models (VLMs) have potential to identify findings on radiologic imaging (i.e., visual parsing) and translate findings into diagnoses (i.e., diagnostic reasoning). Current VLMs have shown insufficient performance to support clinical integration.