Deep learning links histology, molecular signatures and prognosis in cancer

Nat Cancer. 2020 Aug;1(8):755-757. doi: 10.1038/s43018-020-0099-2.

Abstract

Deep learning can be used to predict genomic alterations based on morphological features learned from digital histopathology. Two independent pan-cancer studies now show that automated learning from digital pathology slides and genomics can potentially decipher broader classes of molecular signatures and prognostic associations across cancer types.

Publication types

  • Comment

MeSH terms

  • Deep Learning*
  • Histological Techniques
  • Humans
  • Neoplasms* / diagnosis
  • Prognosis