Prognosis Prediction of Asthma Based on Knowledge Representation Learning of Medical Knowledge Graph
To realize the correct prognosis prediction of home monitoring for asthma patients,combined with medi-cal knowledge graph,representation learning model and neural network method,the prediction model of asthma prog-nosis was constructed.Firstly the model constructs the knowledge graph of asthma patients and disease,and the vector map of the two knowledge graphs was carried out by introducing the representation learning model.Then,the patient and disease vector matrix after concatenation were predicted by the Convolutional Neural Network algorithm.Simula-tion results show that the home monitoring data of asthma patients obtained in this paper and the Global Initiative for Asthma(GINA)data expanded and included on the basis of existing multi-source data effectively alleviated the data sparseness of asthma patients and disease knowledge graph;the TransR-CNN(TRC)model proposed in this paper has a good predictive effect on the prognosis of asthma disease,with an accuracy of 94%,which improves the computation-al efficiency and prediction accuracy.
万方数据
维普
