文献类型：期刊文献

英文题名：An Effective Standardization Method for the Lab Indicators in Regional Medical Health Platform Using N-grams and Stacking

作者：Zhang, Jiaying[1]; Wang, Qi[1]; Zhang, Zhixing[1]; Zhou, Yangming[1]; Ye, Qi[1]; Zhang, Huanhuan[1]; Qiu, Jiahui[1]; He, Ping[2]

机构：[1] School of Information Science and Engineering, East China University of Science and Technology, Shanghai, 200237, China; [2] Shanghai Hospital Development Center, Shanghai, 200041, China

年份：2018

起止页码：1602

外文期刊名：Proceedings - 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018

收录：EI(收录号：20191006610108)

语种：英文

外文关键词：Standardization - Hospitals - Iterative methods - Laboratories - Health

摘要：Since 2008, a regional medical health platform has been built for managing electronic health records of top public hospitals in Shanghai. However, public hospitals often use different names to present a same laboratory examination item (or lab indicator) in this regional platform, which seriously hinders the interconnection and sharing of medical information among hospitals. In this paper, we propose an effective method to standardize the lab indicators using n-gram features and Stacking mechanism. Our proposed method sequentially combines a clustering model and a binary classification model. More specifically, we first cluster the lab indicators based on character uni-gram similarity distances to reduce the alignment scale, and then leverage a binary classification algorithm through Stacking mechanism based on character n-gram similarity features to generate candidate-standard indicator pairs iteratively. Experimental studies on the clinical data collected from eight top public hospitals in Shanghai show that our proposed method achieves a good performance 88.43% in terms of F1-score in the final binary classification, which is highly competitive performance compared to baseline methods. ? 2018 IEEE.