arXiv AI By Shubham Innani, Suhang You, Adam Shephard, Bhakti Baheti, Francesco Ciompi, Joe Yeong, Nasir Rajpoot, Michael Feldman, Solene Florence Kammerer-Jacquet, Dimitrios Makris, Geert Litjens, Anne L. Martel, Jana Lipkova, April Khademi, Spyridon Bakas, for the MICCAI SIG-CompPath

Explainable Artificial Intelligence (XAI) in Computational Pathology: Definitions, Taxonomy, and Recommendations

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arXiv AI
Aug 19

A Multimodal Agentic Pathology Co-pilot via Evidence Grounded Reasoning

PathPocket is a multimodal AI co‑pilot that grounds pathology decision‑making in evidence. It builds the largest pathology evidence corpus (≈110,472 documents) and a hypergraph of 4.55 million entities and 7.10 million relations to support traceable reasoning. The system handles text and multimodal queries, including ROI and gigapixel whole‑slide images, and outperforms current state‑of‑the‑art models on a benchmark of over 200,000 real‑world cases, improving pathologists’ diagnostic accuracy and confidence.

By Zhe Xu, Zhengyu Zhang, Zhiyuan Cai, Jiahao Xu, Yijie Lin, Ziyi Liu, Junlin Hou, Hongyi Wang, Yuxiang Nie, Yihui Wang, Jiabo Ma, Ling Liang, Yingxue Xu, Zhengrui Guo, Guanghao Wu, Danyi Li, Ziqi Zhou, Donglin Tan, Zhijian Cen, Ying Tan, Xiaolin Liu, Qi Xie, Xiaoying Tang, Xi Peng, Cheng Deng, Lijuan Qu, Ronald Cheong Kin Chan, Li Liang, Hao Chen
arXiv AI
Aug 26

LUCAID: Agentic Multimodal AI for Lung Cancer Precision Pathology

LUCAID is an agentic multimodal AI system designed for precision lung cancer pathology, integrating nine modules that cover the entire routine workflow—from quality control and tumor detection to histological subtyping, microenvironment profiling, cellularity quantification, and biomarker scoring (PD‑L1, MET, TROP‑2). The system generates automated structured reports and allows interactive querying of module outputs. In prospective clinical validation, LUCAID achieved 93.0% concordance with an expert‑panel reference standard for clinically actionable decisions, outperforming five experienced thoracic pathologists who ranged from 68.3% to 81.1% concordance.

By Marie-Lisa Eich, Kai Standvoss, Timo Milbich, Alexander M\"ollers, Miriam H\"agele, Philipp Anders, Lars Tharun, Hanna Kontradiuk, Sebastian Kons, Nader Aldoj, Recepcan Adig\"uzel, Adam Narai, Lukas H\"onig, Jonathan Striebel, Binru Yang, Mihnea P. Dragomir, Marvin Sextro, Philipp Keyl, Philipp Jurmeister, Rosemarie Krupar, Evelyn Ramberger, James Wells, Julika Ribbat-Idel, Andreas Kunft, Hussam Shuaib, Christian Groh\'e, Reinhard B\"uttner, David Horst, Klaus-Robert M\"uller, Lukas Ruff, Maximilian Alber, Frederick Klauschen, Simon Schallenberg