Jhep_publication

Our paper on predicting intrahepatic cholangiocarcinoma transcriptomic classes from routine histology using self-supervised learning is published in JHEP Reports! Beyond validating SSL-based molecular subtyping on both biopsies and surgical specimens, we uncover an intriguing influence of training-set constitution: good molecular alignment appears more beneficial than raw data quantity for learning meaningful representations.