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Review
. 2023 Jan;82(1):198-210.
doi: 10.1111/his.14820.

Artificial intelligence in breast cancer histopathology

Ronald Ck Chan  1 , Chun Kit Curtis To  1 , Ka Chuen Tom Cheng  1 , Tada Yoshikazu  1 , Lai Ling Amy Yan  1 , Gary M Tse  1
Affiliations
Review

Artificial intelligence in breast cancer histopathology

Ronald Ck Chan et al. Histopathology. 2023 Jan.

Abstract

This is a review on the use of artificial intelligence for digital breast pathology. A systematic search on PubMed was conducted, identifying 17,324 research papers related to breast cancer pathology. Following a semimanual screening, 664 papers were retrieved and pursued. The papers are grouped into six major tasks performed by pathologists-namely, molecular and hormonal analysis, grading, mitotic figure counting, ki-67 indexing, tumour-infiltrating lymphocyte assessment, and lymph node metastases identification. Under each task, open-source datasets for research to build artificial intelligence (AI) tools are also listed. Many AI tools showed promise and demonstrated feasibility in the automation of routine pathology investigations. We expect continued growth of AI in this field as new algorithms mature.

Keywords: artificial intelligence; breast cancer; literature review.

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