16 citations · 16 across the 7 of their papers we have counts for
3 papers · 1 filter
To What Extent Do Token-Level Representations from Pathology Foundation Models Improve Dense Prediction?
Weiming Chen, Xitong Ling, Xidong Wang +10
Pathology foundation models (PFMs) have rapidly advanced and are becoming a common backbone for downstream clinical tasks, offering strong transferability across tissues and instit…
DiagR1: A Vision-Language Model Trained via Reinforcement Learning for Digestive Pathology Diagnosis
Minxi Ouyang, Lianghui Zhu, Yaqing Bao +10
Multimodal large models have shown great potential in automating pathology image analysis. However, current multimodal models for gastrointestinal pathology are constrained by both…
Subspecialty-Specific Foundation Model for Intelligent Gastrointestinal Pathology
Lianghui Zhu, Xitong Ling, Minxi Ouyang +24
Gastrointestinal (GI) diseases represent a clinically significant burden, necessitating precise diagnostic approaches to optimize patient outcomes. Conventional histopathological d…