计算机应用与软件2024，Vol.41Issue(5)：138-146,9.DOI:10.3969/j.issn.1000-386x.2024.05.022
基于CNN和双向LSTM的房颤预测模型
PREDICTION MODEL OF ATRIAL FIBRILLATION BASED ON CNN AND BIDIRECTIONAL LSTM
摘要
Abstract
The existing model based on CNN cannot extract the temporal characteristics from patient data,while the models based on recurrent neural network ignore the different characteristics of various medical variables.To solve these problems,a predictive model of atrial fibrillation(AF)combined with CNN and RNN is proposed.This model used an independent CNN module to capture the different characteristics among medical variables in the electronic health records(EHR)data.At the same time,an independent RNN module was used to capture the temporal characteristics and correlation characteristics among medical variables in the EHR data.Experimental results on real hospital data sets show that compared with some of the latest disease prediction methods based on EHR data,the model performs better in predicting AF,with an increase of 2.14％in F1 and 1.32％in AUC.关键词
心房颤动/疾病预测/电子病历/卷积神经网络/长短时间记忆网络Key words
Atrial fibrillation/Disease prediction/Electronic health records/Convolutional neural network/Long short-term memory分类
医药卫生引用本文复制引用
吴石远,陈艳红,杨湘,高峰,顾进广..基于CNN和双向LSTM的房颤预测模型[J].计算机应用与软件,2024,41(5):138-146,9.基金项目
国家自然科学基金项目(U1836118) （U1836118）
教育部新一代信息技术创新项目(2018A03025). （2018A03025）
