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

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

collaborators

9 papers

cs.CV2026

A Pathology Foundation Model for Gastric Cancer with Real-World Validation

Ling Liang, Jiabo Ma, Zhengyu Zhang +25

Gastric cancer remains a major cause of cancer mortality, yet its histological and molecular heterogeneity complicates diagnosis and risk stratification. General-purpose pathology…

cs.LG2026

Spatial Transcriptomics-Guided Alignment Enhances Molecular Profiling in Pathology Foundation Model

Fengtao Zhou, Yingxue Xu, Zhengyu Zhang +20

Comprehensive molecular profiling is essential for modern precision oncology but remains hindered by prohibitive costs, specimen exhaustion, and protracted turnaround times. While…

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…

eess.IV2026

A Clinically Validated Foundation Model for Comprehensive Lung Pathology Interpretation

Zhengrui Guo, Zhengyu Zhang, Jiabo Ma +23

Pathological assessment guides lung cancer diagnosis, treatment selection, and prognostic evaluation, yet current CPath approaches rely on task-specific models for isolated objecti…

cs.CV2026

A Deployment-Friendly Foundational Framework for Efficient Computational Pathology

Yu Cai, Cheng Jin, Zhengyu Zhang +25

Pathology foundation models (PFMs) generalize well across computational pathology tasks but remain costly for gigapixel whole-slide image analysis. Here, we present LitePath, a dep…

cs.CV2025

MambaMIL+: Modeling Long-Term Contextual Patterns for Gigapixel Whole Slide Image

Qian Zeng, Yihui Wang, Shu Yang +9

Whole-slide images (WSIs) are an important data modality in computational pathology, yet their gigapixel resolution and lack of fine-grained annotations challenge conventional deep…

eess.IV2025

A Versatile Pathology Co-pilot via Reasoning Enhanced Multimodal Large Language Model

Zhe Xu, Ziyi Liu, Junlin Hou +13

Multimodal large language models (MLLMs) have emerged as powerful tools for computational pathology, offering unprecedented opportunities to integrate pathological images with lang…

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…