{"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.
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