实用医学杂志2025，Vol.41Issue(14)：2160-2166,7.DOI:10.3969/j.issn.1006-5725.2025.14.006
深度学习在早期胃癌内镜图像诊断中的研究进展
Advances in deep learning for endoscopic image-based diagnosis of early gastric cancer
摘要
Abstract
Gastric carcinoma(GC),a highly prevalent malignant tumor globally,often progresses to advanced stages by the time of diagnosis due to its insidious clinical presentation,thereby significantly reducing therapeutic effectiveness and patient quality of life.Accurate screening and histopathological characterization of early gastric cancer(EGC)are essential for developing individualized treatment approaches.Although endoscopic techniques remain the gold standard for early GC detection,their diagnostic accuracy is largely dependent on the operator's skill,a challenge that current artificial intelligence(AI)-assisted innovations aim to address by stan-dardizing diagnostic procedures.Deep learning(DL)-based computer vision systems have demonstrated remarkable performance in identifying subtle EGC features,not only improving lesion detection sensitivity but also enabling automated assessment of key pathological indicators.These technological advances offer objective,visualized diag-nostic support for clinical decision-making.This review provides a systematic overview of recent developments in DL applications for endoscopic image analysis of EGC and evaluates their potential for clinical integration.关键词
早期胃癌/深度学习/内镜图像Key words
early gastric cancer/deep learning/endoscopic images分类
医药卫生引用本文复制引用
张倩,曹云太,王志洁,周伯琪..深度学习在早期胃癌内镜图像诊断中的研究进展[J].实用医学杂志,2025,41(14):2160-2166,7.基金项目
医学影像中心国家级临床重点专科项目(编号:202490) （编号:202490）
