基于图嵌入的个性化心力衰竭管理运动处方推荐系统构建

Construction of a Graph Embedding Recommendation System for Personalized Exercise Prescription in Heart Failure Management

目的/意义促进心力衰竭(heart failure,HF)管理运动训练的临床实践。方法/过程系统分析并整合相关文献、临床指南及专家共识,构建HF与运动训练知识图谱(knowledge graph,KG)。基于该KG,采用快速随机投影算法和K-邻近算法,构建图嵌入的推荐模型和个性化HF管理运动处方推荐系统。结果/结论HF与运动训练的KG共包括2703个实例和25161条关系。基于该KG,图嵌入的个性化推荐系统可提供安全、有效、多样的运动处方推荐。

Purpose/Significance To promote the clinical practice of exercise training intervention in the management of heart failure(HF).Method/Process The relevant literatures,clinical guidelines,and expert consensus are systematically analyzed and integrated,and a knowledge graph(KG)of HF and exercise training is constructed.Based on the KG,a graph embedding recommendation model and a personalized exercise prescription recommendation system for the management of HF are constructed by using the fast random projection algorithm and the K-nearest neighbors algorithm.Result/Conclusion In total,the KG of HF and exercise training includes 2703 instances and 25161 relations.Based on the KG,the graph-embedded personalized recommendation system provides safe,effective,and diverse exercise prescription recommendations.