Digitisation of vast archives of histology slides provides opportunities to use machine learning to identify specific tissue substructures associated with disease. Here the authors use self-supervised learning on 1.7 million histology images from 23 human tissues. The model segments tissues, detects pathologies and predicts RNA expression, linking morphology and gene expression.
- Francesco Cisternino
- Sara Ometto
- Craig A. Glastonbury
