Artificial intelligence in breast pathology - dawn of a new era

• Type of Material: Article
• Authors: Sunil Badve, Emory University
• Language: English
• Date: 2023-01-31
• Publisher: NATURE PORTFOLIO
• Publication Version: Final Published Version
• Copyright Statement: © The Author(s) 2023
• License: Creative Commons Attribution 4.0 International
• Final Published Version (URL): http://dx.doi.org/10.1038/s41523-023-00507-4
• Title of Journal or Parent Work: NPJ BREAST CANCER
• Volume: 9
• Issue: 1
• Start Page: 5
• End Page: 5
• Keywords: Life Sciences & Biomedicine; Science & Technology; Oncology
• Research Categories: Health Sciences, Pathology

Abstract

Artificial intelligence methods are been increasingly used for analysis of pathology slides. In this issue of the Journal, Sandbank et al. describe the validation and utility of a robust second reader system that can distinguish in situ and standfirst invasive carcinomas from non-neoplastic lesions of the breast.