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If you 're attending this year's EASL meeting, don't forget to attend the basic session this afternoon, Yue will present our study on the use of AI to ease ICCA diagnosis: Jansen - Hall 8.0 Friday, 29 May, 17:45 - 18:00 CEST

Diagnosing Intrahepatic Cholangiocarcinoma (ICCA) is a major clinical hurdle. Because its histological features closely overlap with those of metastatic liver cancers, patients often endure a battery of expensive and invasive tests—such as endoscopies—to rule out other primary tumor sites. These "exclusionary investigations" lead to critical treatment delays and increased healthcare costs. Here we performed a multi-center study that involved the development of AI2CCA (Artificial Intelligence for ICCA diagnosis), a deep-learning model designed to solve this exact problem using routine liver biopsy slides. We also prospectively validate it on 4 centers across the globe. Unlike traditional "black box" AI, AI2CCA uses a confidence-based framework (G-ODIN) that allows the model to abstain from a prediction when uncertainty is too high.

Qinghe Zeng will present our work ''Spatial profiling of hepatocellular carcinoma identifies distinct tumor and immune micro-ecosystems related to patient outcomes'' at the ILCA 2025 conference, as an oral communication during the General Session 1 - Molecular Pathogenesis, Cell Biology and Translational Spatial transcriptomics heat map of a Hepatocellular Carcinoma Research

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