数字中医药（英文）2025，Vol.8Issue(2)：163-173,11.DOI:10.1016/j.dcmed.2025.05.005
基于自适应权重多模态中西医数据融合方法的冠心病血管阻塞程度预测模型的构建与评价
Construction and evaluation of a predictive model for the degree of coronary artery occlusion based on adaptive weighted multi-modal fusion of traditional Chinese and western medicine data
摘要
Abstract
Objective To develop a non-invasive predictive model for coronary artery stenosis severity based on adaptive multi-modal integration of traditional Chinese and western medicine data. Methods Clinical indicators,echocardiographic data,traditional Chinese medicine(TCM)tongue manifestations,and facial features were collected from patients who underwent coro-nary computed tomography angiography(CTA)in the Cardiac Care Unit(CCU)of Shanghai Tenth People's Hospital between May 1,2023 and May 1,2024.An adaptive weighted multi-modal data fusion(AWMDF)model based on deep learning was constructed to predict the severity of coronary artery stenosis.The model was evaluated using metrics including accura-cy,precision,recall,F1 score,and the area under the receiver operating characteristic(ROC)curve(AUC).Further performance assessment was conducted through comparisons with six ensemble machine learning methods,data ablation,model component ablation,and various decision-level fusion strategies. Results A total of 158 patients were included in the study.The AWMDF model achieved ex-cellent predictive performance(AUC=0.973,accuracy=0.937,precision=0.937,recall=0.929,and F1 score=0.933).Compared with model ablation,data ablation experiments,and various traditional machine learning models,the AWMDF model demonstrated superior per-formance.Moreover,the adaptive weighting strategy outperformed alternative approaches,including simple weighting,averaging,voting,and fixed-weight schemes. Conclusion The AWMDF model demonstrates potential clinical value in the non-invasive prediction of coronary artery disease and could serve as a tool for clinical decision support.关键词
冠心病/深度学习/多模态/临床预测/中医诊断Key words
Coronary artery disease/Deep learning/Multi-modal/Clinical prediction/Traditional Chinese medicine diagnosis引用本文复制引用
张冀豫,许家佗,屠立平,付洪媛..基于自适应权重多模态中西医数据融合方法的冠心病血管阻塞程度预测模型的构建与评价[J].数字中医药（英文）,2025,8(2):163-173,11.基金项目
Construction Program of the Key Discipline of State Ad-ministration of Traditional Chinese Medicine of China(ZYYZDXK-2023069),Research Project of Shanghai Mu-nicipal Health Commission(2024QN018),and Shanghai University of Traditional Chinese Medicine Science and Technology Development Program(23KFL005). （ZYYZDXK-2023069）
