collaborators

14 papers

cs.AI2026

Democratizing and accelerating AI-driven pathology research through agentic intelligence

Jiabo Ma, Cheng Jin, Yihui Wang +19

Computational pathology has advanced rapidly with the emergence of foundation models, yet widespread adoption remains limited by substantial technical complexity and programming re…

cs.AI2026

A Multimodal Agentic Pathology Co-pilot via Evidence Grounded Reasoning

Zhe Xu, Zhengyu Zhang, Zhiyuan Cai +26

Pathology is the cornerstone of modern medicine, where accurate decision-making relies heavily on evidence-based practices. While artificial intelligence (AI) has the potential to…

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.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.CV2026

A Deployment-Friendly Foundational Framework for Efficient Computational Pathology

Yu Cai, Cheng Jin, Jiabo Ma +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

Generative AI for Misalignment-Resistant Virtual Staining to Accelerate Histopathology Workflows

Jiabo MA, Wenqiang Li, Jinbang Li +7

Accurate histopathological diagnosis often requires multiple differently stained tissue sections, a process that is time-consuming, labor-intensive, and environmentally taxing due…