activity
20242026
most citedA Multimodal Knowledge-enhanced Whole-slide Pathology Foundation Model

9 citations · 12 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2026

A Breast Vision Pathology Foundation Model for Real-world Clinical Utility

Yingxue Xu, Zhengyu Zhang, Xiuming Zhang +32

Pathology foundation models have shown strong retrospective performance, but whether such systems can support clinically relevant use remains unclear. This challenge is particularl…

cs.LG2025

A Multimodal Foundation Model to Enhance Generalizability and Data Efficiency for Pan-cancer Prognosis Prediction

Huajun Zhou, Fengtao Zhou, Jiabo Ma +6

Multimodal data provides heterogeneous information for a holistic understanding of the tumor microenvironment. However, existing AI models often struggle to harness the rich inform…

cs.CV2025

Genome-Anchored Foundation Model Embeddings Improve Molecular Prediction from Histology Images

Cheng Jin, Fengtao Zhou, Yunfang Yu +13

Precision oncology requires accurate molecular insights, yet obtaining these directly from genomics is costly and time-consuming for broad clinical use. Predicting complex molecula…

cs.CV2025★ 3 cited

PathBench: A comprehensive comparison benchmark for pathology foundation models towards precision oncology

Jiabo Ma, Yingxue Xu, Fengtao Zhou +23

The emergence of pathology foundation models has revolutionized computational histopathology, enabling highly accurate, generalized whole-slide image analysis for improved cancer d…

cs.CV2024★ 9 cited

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…