基于多核学习的电子病历多视图聚类研究及应用  

Research and application of multi-view clustering of electronic health records based on multi-kernel learning

作　　者：陈薇薇 蒋翔 孙朝玮 Chen Weiwei;Jiang Xiang;Sun Chaowei(Shanghai Jing’an District Central Hospital,Shanghai 200072,China)

机构地区：[1]上海市静安区闸北中心医院,上海200072

出　　处：《现代计算机》2024年第13期63-67,共5页Modern Computer

摘　　要：电子病历的分析和应用是智慧医疗领域研究的热点,提出一种基于多核学习的电子病历多视图聚类模型,对多核学习挖掘电子病历的非线性相关信息和高阶相关性信息、利用谱聚类对融合的核矩阵(相似性矩阵)进行聚类研究,得到多视图数据空间的聚类结果。实验结果表明,该方法能快速准确地对电子病历中的信息进行聚类,在性能指标上优于其它方法。The analysis and application of electronic medical records is a hot topic in the field of smart healthcare.A multi view clustering model for electronic medical records based on multi kernel learning is proposed.The model utilizes multi kernel learning to mine nonlinear and high-order correlation information of electronic medical records,and spectral clustering to fuse the kernel matrix(similarity matrix)for clustering research.The clustering results of the multi view data space are obtained.The experimental results show that this method can quickly and accurately cluster information in electronic medical records,and is superior to other methods in terms of performance indicators.

关 键 词：多核学习 电子病历 多视图聚类 

分 类 号：R-05[医药卫生] TP18[自动化与计算机技术—控制理论与控制工程] TP311.13[自动化与计算机技术—控制科学与工程]