A Survey on Knowledge Enhanced EHR Data Mining

Jiancheng Zhang, Xiao Yang, Hefeng Meng, Zhiqiang Lin, Yonghui Xu, Lizhen Cui

Abstract: EHR contains detailed information about a large number of patients. In the past ten years, EHR-related research has involved various fields, and research in various fields is inseparable from the acquisition of knowledge in EHR. The rapid development of various fields in recent years has brought new challenges to the acquisition of knowledge in EHR. At the same time, the knowledge enhancement technology that has emerged in recent years has effectively improved this problem. Therefore, more and more researches personnel applied knowledge enhancement technology to EHR. In this article, we summarized the literature in this area. We first summarized the knowledge types of EHR, and then made a sub-statement on knowledge extraction and modeling. Next, the correct representation method of knowledge is given, and finally, the specific application in each field is summarized. We hope this article can continue to promote the development of knowledge enhancement technology in EHR.