时珍国医国药2026，Vol.37Issue(5)：993-1000,8.DOI:10.70976/j.1008-0805.SZGYGY-2026-0529
"智""镜"联合——探索慢性胃炎的中西医诊断与辨证
Exploring the diagnosis and syndrome differentiation of chronic gastritis with Chinese and Western medicine based on machine learning and gastroscopy
摘要
Abstract
Objective To explore the classification diagnosis and syndrome differentiation of chronic gastritis(CG)based on various machine learning models using gastroscopic images,and to assess its value for theoretical innovation in the diagnosis of Chinese and Western medicine.Methods From June 2023 to March 2024,2,052 gastroscopic images from patients diagnosed with CG were retro-spectively collected at Hebei Provincial Hospital of Traditional Chinese Medicine.After data preprocessing,three machine learning models were established to evaluate the value of machine learning-assisted gastroscopy for diagnosing CG.As an supplement of tradi-tional Chinese medicine(TCM)inspection,gastroscopy was utilized.From the original dataset,2016 gastroscopic images were selected to form a new dataset.Based on machine learning,deficiency-excess syndrome differentiation was performed to explore the role of gas-troscopy in TCM syndrome differentiation of CG.Results The accuracy rates of the three gastroscopy-based models(ViT,ResNet50,VGG16)we trained for chronic atrophic gastritis(CAG)were 98.60%,95.16%,and 95.81%,respectively.For chronic non-atrophic gastritis(CNAG),the accuracies were 99.16%,99.58%,and 99.16%,respectively.In further experiments,the four machine learn-ing models(ViT,ResNet50,VGG16,MobileNet)achieved accuracies of 95.09%,88.24%,90.20%,and 87.25%for identifying the CG excess syndrome group,and 89.10%,88.11%,89.14%,and 91.09%for the CG deficiency syndrome group,respectively.Con-clusion This study demonstrates that machine learning can serve as a reliable method to assist in the gastroscopic diagnosis of CG.Fur-thermore,the gastroscopy-based machine learning diagnostic model we developed can be used for TCM syndrome differentiation of CG.Machine learning can assist physicians in disease classification and syndrome differentiation,offering clinical value for human-computer collaborative decision-making.关键词
慢性胃炎/机器学习/胃镜下辨证/Vision Transformer/ResNet50Key words
Chronic gastritis/Machine learning/Gastroscopic syndrome differentiation/Vision transformer/ResNet50分类
医药卫生引用本文复制引用
段雨萌,于倩茹,张柳盟,康丽洁,张坤,支政,杨倩,徐伟超.."智""镜"联合——探索慢性胃炎的中西医诊断与辨证[J].时珍国医国药,2026,37(5):993-1000,8.基金项目
国家自然科学基金(82205314) （82205314）
癌症、心脑血管、呼吸和代谢性疾病防治研究国家科技重大专项(2024ZD0521004) （2024ZD0521004）
中华中医药学会脾胃病分会青年培英计划(中会学术[2025]2号) （中会学术[2025]2号）
河北省省级科技计划资助项目(246W7701D) （246W7701D）
河北省"岐黄赤子"培养工程(冀中医药函[2025]1号) （冀中医药函[2025]1号）
河北省高等教育教学改革研究与实践项目(2023GJJG287) （2023GJJG287）
