电子科技2026，Vol.39Issue(6)：54-62,9.DOI:10.16180/j.cnki.issn1007-7820.2026.06.007
基于A-CNN-LSTM模型的静脉壶凝血等级在线预测
Online Prediction of Venous Chamber Hemostasis Level Based on the A-CNN-LSTM Model
摘要
Abstract
Coagulation is a common complication during hemodialysis.In severe cases,it can easily lead to ir-reversible waterfall coagulation reactions.Therefore,predicting the occurrence of coagulation in advance is of great significance for ensuring the dialysis effect and life safety of patients.A coagulation grade prediction model A-CNN-LSTM(Attention-Convolutional Neural Network-Long Short-Term Memory)based on the image sequence of dialysis venous kettles is proposed to predict the coagulation grade of patients with nephropathy during dialysis online.Under the condition of ensuring the same prediction accuracy,the A-CNN-LSTM model can predict the coagulation grade for a longer time using a shorter image sequence,and the prediction accuracy of the coagulation grade for patients can reach 93.5%.Compared with the traditional prediction models LSTM and CNN-LSTM,the prediction accuracy of the proposed model has increased by 9.9 percentage points and 5.3 percentage points,respectively.After tripling the number of input frames,the prediction accuracy of the A-CNN-LSTM model reaches 94%.The experimental results show that extracting the coagulation features of venous kettles through multi-scale convolution can solve the uncertain-ty problems of the input coagulation images,the shape and size of the blood coagulation area,and also can improve the prediction accuracy.Integrating the attention mechanism into the proposed model improves the accuracy of weight distribution,accelerates the convergence speed of errors and reduces the error value.关键词
血液透析/凝血等级预测/卷积神经网络/长短期记忆/注意力机制/多尺度/静脉壶图像/预测模型Key words
hemodialysis/hemostasis level prediction/convolutional neural network/long short-term memory/attention mechanism/multi-scale/venous chamber images/prediction model分类
信息技术与安全科学引用本文复制引用
倪硕,李一鸣,邵青,刘盈秀,刘楠梅,杨晖..基于A-CNN-LSTM模型的静脉壶凝血等级在线预测[J].电子科技,2026,39(6):54-62,9.基金项目
国家自然科学基金(12372384,12072200) （12372384,12072200）
上海理工大学高水平大学建设医工交叉项目(海军特色医学中心)(1022302504)National Natural Science Foundation of China(12372384,12072200) （海军特色医学中心）
University of Shanghai for Science and Technology High-Level Univer-sity Construction Biomedical Engineering Interdisciplinary Project(Naval Medical Center of PLA)(1022302504) （Naval Medical Center of PLA）
