“Researchers developed a foundational vision-language model trained on radiologist eye-tracking data and diagnostic reasoning to better bridge the gap between AI outputs and expert clinical workflows. This approach moves beyond standard semantic optimization to emulate how radiologists actually examine chest X-rays, potentially improving clinical utility and diagnostic accuracy of AI systems in medical imaging.”