Categorization of Patient Disease into ICD-10 with NLP and SVM for Chinese Electronic Health Record Analysis

J. Zhong, Chuangui Gao, X. Yi
{"title":"Categorization of Patient Disease into ICD-10 with NLP and SVM for Chinese Electronic Health Record Analysis","authors":"J. Zhong, Chuangui Gao, X. Yi","doi":"10.1145/3268866.3268877","DOIUrl":null,"url":null,"abstract":"The electronic health record (EHR) analysis has become an increasingly important application for artificial intelligence (AI) algorithms to leverage the insight from the big data for improving the quality of human healthcare. In a lot of Chinese EHR analysis applications, it is very important to categorize the patients' diseases according to the medical coding standard. In this paper, we develop NLP and machine learning algorithms to automatically categorize each patient's individual diseases into the ICD-10 coding standard. Experimental results show that the support vector machine algorithm (SVM) accomplishes very promising classification results.","PeriodicalId":285628,"journal":{"name":"Proceedings of the 2018 International Conference on Artificial Intelligence and Pattern Recognition","volume":"18 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2018 International Conference on Artificial Intelligence and Pattern Recognition","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3268866.3268877","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7

Abstract

The electronic health record (EHR) analysis has become an increasingly important application for artificial intelligence (AI) algorithms to leverage the insight from the big data for improving the quality of human healthcare. In a lot of Chinese EHR analysis applications, it is very important to categorize the patients' diseases according to the medical coding standard. In this paper, we develop NLP and machine learning algorithms to automatically categorize each patient's individual diseases into the ICD-10 coding standard. Experimental results show that the support vector machine algorithm (SVM) accomplishes very promising classification results.
基于NLP和SVM的中国电子病历分类研究
电子健康记录(EHR)分析已成为人工智能(AI)算法越来越重要的应用,它利用大数据的洞察力来提高人类医疗保健的质量。在中国的电子病历分析应用中,根据医学编码标准对患者的疾病进行分类是非常重要的。在本文中,我们开发了NLP和机器学习算法来自动将每个患者的个体疾病分类到ICD-10编码标准中。实验结果表明,支持向量机算法取得了很好的分类效果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信