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WILSON - a pathology foundation model framework for patient-level analysis and diagnostic text generation
Pathologists integrate morphology across magnifications and across the slides of a patient case, whereas pathology foundation models encode thousands of tiles from single slides and aggregate their features. Here we present WILSON, a vision--language foundation model that represents whole-slide images and multi-slide cases as single multi-magnification composite images, trained on approximately 189k slides from Mayo Clinic spanning 42 organs and 829 diagnostic entities using pathology reports as supervision. Without task-specific training, WILSON exceeded a dedicated case-level model on all in
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-20T16:01:04.000Z
First collected: 2026-09-23T09:51:33.063Z. This is not the publication date.