A histomorphological atlas of resected mesothelioma discovered by self-supervised learning from 3446 whole-slide images
Farzaneh Seyedshahi, Kai Rakovic, Nicolas Poulain, Adalberto Claudio Quiros, Ian R. Powley, Cathy J. Richards, Hussein Uraiby, Sonja Klebe, David Allan Moore, Apostolos Nakas, Claire Wilson, Marco Sereno, Leah Officer-Jones, Catherine Ficken, Ana Teodòsio, , John P. C. Le Quesne
This paper uses self-supervised learning on 3446 H&E-stained mesothelioma slides to create a histomorphological atlas, achieving high predictive performance and revealing molecular insights.
Nature Communications · Oct 7, 2025Peer-reviewedPathology