Applications of Deep Learning in Endocrine Neoplasms

Surg Pathol Clin. 2023 Mar;16(1):167-176. doi: 10.1016/j.path.2022.09.014. Epub 2022 Dec 12.


Machine learning methods have been growing in prominence across all areas of medicine. In pathology, recent advances in deep learning (DL) have enabled computational analysis of histological samples, aiding in diagnosis and characterization in multiple disease areas. In cancer, and particularly endocrine cancer, DL approaches have been shown to be useful in tasks ranging from tumor grading to gene expression prediction. This review summarizes the current state of DL research in endocrine cancer histopathology with an emphasis on experimental design, significant findings, and key limitations.

Keywords: Deep learning; Endocrine neoplasia; Histology; Machine learning; Pathology.

Publication types

  • Review

MeSH terms

  • Deep Learning*
  • Endocrine Gland Neoplasms* / diagnosis
  • Humans
  • Machine Learning
  • Medicine*
  • Neoplasms*