Biological insights and novel biomarker discovery through deep learning approaches in breast cancer histopathology.

ABSTRACT: Breast cancer remains a highly prevalent disease with considerable inter- and intra-tumoral heterogeneity complicating prognostication and treatment decisions. The utilization and depth of genomic, transcriptomic and proteomic data for cancer has exploded over recent times and the addition of spatial context to this information, by understanding the correlating morphologic and spatial patterns of cells in tissue samples, has created an exciting frontier of research, histo-genomics. At the same time, deep learning (DL), a class of machine learning algorithms employing artificial neural networks, has rapidly progressed in the last decade with a confluence of technical developments - including the advent of modern graphic processing units (GPU), allowing efficient implementation of increasing

SUBMITTER: Mandair D 

PROVIDER: S-EPMC10079681 | biostudies-literature | 2023 Apr

REPOSITORIES: biostudies-literature