Yousif Mustafa, Pantanowitz Liron
Department of Pathology, University of Michigan, NCRC Building 35, 2800 Plymouth Road, Ann Arbor, MI 48109, USA.
Department of Pathology, UPMC Shadyside Hospital, 5150 Centre Avenue Cancer Pavilion, POB2, Suite 3B, Room 347, Pittsburgh, PA 15232, USA.
Surg Pathol Clin. 2023 Dec;16(4):673-686. doi: 10.1016/j.path.2023.05.005. Epub 2023 Jul 18.
The integration of digital pathology and artificial intelligence (AI) is revolutionizing pathology by providing pathologists with new tools to improve workflow, enhance diagnostic accuracy, and undertake novel discovery. The capability of AI to recognize patterns and features in digital images beyond human perception is particularly valuable, thereby providing additional information for prognostic and predictive purposes. AI-based tools diagnose gastric carcinoma in digital images, detect gastric carcinoma metastases in lymph nodes, automate Ki-67 scoring in gastric neuroendocrine tumors, and quantify tumor-infiltrating lymphocytes. This article provides an overview of all of these applications of AI pertaining to gastric cancer.
数字病理学与人工智能（AI）的整合正在彻底改变病理学，为病理学家提供新工具以改善工作流程、提高诊断准确性并进行新的发现。人工智能识别数字图像中超出人类感知的模式和特征的能力尤为宝贵，从而为预后和预测目的提供额外信息。基于人工智能的工具可在数字图像中诊断胃癌、检测淋巴结中的胃癌转移、自动对胃神经内分泌肿瘤进行Ki-67评分以及量化肿瘤浸润淋巴细胞。本文概述了人工智能在胃癌方面的所有这些应用。
