A BERT model generates diagnostically relevant semantic embeddings from pathology synopses with active learning.

We provide a generalizable deep learning model and approach to unlock the semantic information inherent in pathology synopses toward improved diagnostics, biodiscovery and AI-assisted computational pathology.