上海中医药杂志2026，Vol.60Issue(4)：1-9,9.DOI:10.16305/j.1007-1334.2026.z20251022001
基于人工智能融合中医舌象、证素及西医指标构建2型糖尿病缓解预测模型
Construction of a predictive model for type 2 diabetes remission based on artificial intelligence integration of traditional Chinese medicine tongue manifestations,syndrome elements and Western medical indicators
摘要
Abstract
Objective To construct a predictive model for the remission of type 2 diabetes through nutritional intervention by integrating traditional Chinese medicine(TCM)tongue manifestation parameters,syndrome elements,and Western medical indicators.Methods A retrospective analysis was conducted on 424 patients who underwent nutritional intervention targeting diabetes remission at the Department of Endocrinology,Shanghai Municipal Hospital of TCM Affiliated to Shanghai University of TCM from 2022 to 2024.Clinical data and tongue images of the patients at baseline and during follow-up were collected.Four types of feature combinations were constructed:Western medical indicators alone,Western medical indicators plus TCM tongue manifestation parameters,Western medical indicators plus TCM syndrome elements,and Western medical indicators plus TCM tongue manifestation parameters plus TCM syndrome elements.Logistic regression,random forest and extreme gradient boosting algorithms were respectively used for model construction,and model performance was evaluated using indicators including the area under the receiver operating characteristic(ROC)curve(AUC).Results The integrated model(Western medical indicators plus TCM tongue manifestation parameters plus TCM syndrome elements)constructed by the random forest algorithm exhibited the optimal predictive performance,with an AUC of 0.95(95%CI:0.92-0.98),which was significantly superior to the model with Western medical indicators alone(AUC=0.89).Variable importance analysis identified fasting C-peptide,body mass index(BMI),quantitative insulin sensitivity check index(QUICKI),body fat percentage,glycated hemoglobin(HbA1c),abdominal fat percentage,as well as TCM tongue manifestation parameters including tongue coating moistness(taiL)and tongue coating color parameter(taiG)as the most important predictive variables.Conclusion This study successfully constructed a machine learning predictive model integrating TCM tongue manifestation parameters,syndrome elements and Western medical indicators,which can identify the advantageous population suitable for achieving diabetes remission through nutritional intervention.关键词
糖尿病缓解/人工智能/机器学习/预测模型/舌诊/中西医结合/营养干预Key words
diabetes remission/artificial intelligence/machine learning/predictive model/tongue diagnosis/integrated traditional Chinese and Western medicine/nutritional intervention引用本文复制引用
黄怡文,张珂,张倩为,曾先昌,朱烨琳,刘珍秀,江涛,陶枫..基于人工智能融合中医舌象、证素及西医指标构建2型糖尿病缓解预测模型[J].上海中医药杂志,2026,60(4):1-9,9.基金项目
上海市卫健委中医药传承创新发展三年行动计划项目[ZY(2025-2027)-1-2-4] （2025-2027）
上海市科委医学创新项目(23Y11921500) （23Y11921500）
国家中医药管理局中医优势专科建设项目-老年病科(RCYS40192025002-Z) （RCYS40192025002-Z）
