Biological Insights And Novel Biomarker Discovery Through Deep Learning Approaches In Breast Cancer Histopathology

Breast cancer is a highly prevalent disease with considerable inter- and intra-tumoral heterogeneity, making prognostication and treatment decisions difficult. Recent advances in deep learning (DL) and histo-genomics have created an exciting frontier of research, with DL being used to extract genomic information and stroma to predict cancer recurrence. This review examines recent developments in the application of DL in breast cancer histology, with the aim of suggesting avenues for further advancing this field.