S. Innani

AI-Based Prognostic Risk Stratification of Adult-Type Diffuse Glioma Patients from H&E-Stained Slides

Background/Objectives: Adult-type diffuse gliomas (ADGs) are aggressive brain tumors with highly variable clinical outcomes. Prognostic assessment directly from routine hematoxylin and eosin (H&E)-stained whole-slide images (WSIs) could support personalized decision-making. Methods: To our knowledge, this is the first...

Multimodal Explainable Arti fi cial Intelligence for Prognostic Strati fi cation of Patients With Glioblastoma

Benchmarking Vision-Language Models for Automated Pathology Diagnosis and Report Generation

A clinically curated Pan-Asia WSI--report dataset is introduced and the REG 2025 benchmark is established as a benchmark for evaluating WSI-based structured report generation and vision-language understanding in computational pathology, providing insights for the design of clinically grounded multimodal pathology model...

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

This review aims to formalize XAI methods in CompPath through the introduction of a pathology-centric vocabulary comprising seven core terms and establishment of a task-driven framework that maps five clinical questions to recommended methods, method evaluation, and deployment context.