A World Model of Radiologist Reading for Medical Image Representation Learning 事件

A World Model of Radiologist Reading for Medical Image Representation Learning arXiv:2605.23992v1 Announce Type: new Abstract: Radiologist eye-tracking data provide a rich record of how experts search, compare, and accumulate evidence during image reading; yet, existing methods exploit this signal only partially, either as a static spatial prior or as an auxiliary prediction target decoupled from diagnosis. We propose GazeWorld, a medical imaging world model that treats the image as the world a