现代中医临床2026，Vol.33Issue(1)：27-32,6.DOI:10.3969/j.issn.2095-6606.2026.01.005
深度学习辅助中医望诊的抑郁症诊断模型研究
Deep learning-assisted diagnosis model of depression based on TCM facial inspection
摘要
Abstract
Objective To develop a deep learning-based facial diagnostic model for depression,providing a novel approach for early recognition of depression through Traditional Chinese Medicine(TCM)facial inspection.Methods A total of 437 participants were enrolled,including 210 patients with depression of the liver-qi stagnation and spleen-deficiency pattern,114 non-depressed individuals with the same TCM pattern,and 113 healthy controls.Facial images were collected following standardized procedures.After excluding blurred,occluded,or abnormally posed images,data augmentation was performed using rotation,scaling,flipping,translation,and Gaussian noise.The dataset was divided into training,validation,and test sets in an 8:1:1 ratio.Classification models were constructed using EfficientNet,MobileNet V3,and ResNet18.Model performance was evaluated in terms of accuracy,parameter size,convergence speed,and confusion matrix.Class activation mapping(CAM)was employed to visualize the regions of facial attention contributing to model decisions.Results(1)EfficientNet achieved the highest accuracy(98.6％),with a moderate parameter size(4.01 M)and fast convergence,followed by MobileNet V3(accuracy 92.7％,1.52 M parameters),while ResNet18 showed the lowest accuracy(92.2％)and the largest parameter size(11.18 M).(2)The confusion matrix revealed that EfficientNet exhibited the lowest misclassification rate among the three groups.(3)CAM visualization demonstrated that EfficientNet not only focused on the periocular region but also on the perioral area when making predictions.Conclusion Deep learning-based facial image analysis can effectively extract depression-related facial expression features,providing objective evidence to support intelligent TCM facial diagnosis and assist in the recognition of depressive disorders.关键词
抑郁症/望诊/面部图像/深度学习/人工智能诊断Key words
depression/TCM inspection diagnosis/facial images/deep learning/artificial intelligence diagnosis分类
医药卫生引用本文复制引用
李红培,韩振蕴,胡文悦,王浛宇,李彦良..深度学习辅助中医望诊的抑郁症诊断模型研究[J].现代中医临床,2026,33(1):27-32,6.基金项目
国家重点研发计划(No.2019YFC1710103) （No.2019YFC1710103）
深圳市"医疗卫生三名工程"项目资助(No.SZZYSM202105010) （No.SZZYSM202105010）
深圳市龙岗区科技创新专项资金医疗卫生技术攻关项目(No.LGKCYLWS2022012) （No.LGKCYLWS2022012）
深圳市龙岗区医学重点学科建设项目 （）
