9 citations · 26 across the 15 of their papers we have counts for
4 papers · 1 filter
Towards A Generalizable Pathology Foundation Model via Unified Knowledge Distillation
Jiabo Ma, Zhengrui Guo, Fengtao Zhou +20
Foundation models pretrained on large-scale datasets are revolutionizing the field of computational pathology (CPath). The generalization ability of foundation models is crucial fo…
A Multimodal Knowledge-enhanced Whole-slide Pathology Foundation Model
Yingxue Xu, Yihui Wang, Fengtao Zhou +16
Remarkable strides in computational pathology have been made in the task-agnostic foundation model that advances the performance of a wide array of downstream clinical tasks. Despi…
GSCo: Towards Generalizable AI in Medicine via Generalist-Specialist Collaboration
Sunan He, Yuxiang Nie, Hongmei Wang +21
Generalist foundation models (GFMs) are renowned for their exceptional capability and flexibility in effectively generalizing across diverse tasks and modalities. In the field of m…
iMD4GC: Incomplete Multimodal Data Integration to Advance Precise Treatment Response Prediction and Survival Analysis for Gastric Cancer
Fengtao Zhou, Yingxue Xu, Yanfen Cui +11
Gastric cancer (GC) is a prevalent malignancy worldwide, ranking as the fifth most common cancer with over 1 million new cases and 700 thousand deaths in 2020. Locally advanced gas…