基于ICD-10的泰国主诉的体征和症状标记

Pawin Saeku, Jarunee Duangsuwan
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引用次数: 3

摘要

本文提出了一种自然语言处理(NLP)方法来构建体征和症状语料库,以识别基于国际疾病和相关健康问题统计分类第十次修订(ICD-10)形式的泰国主诉(cc)中记录的体征和症状。在我们的作品中,我们将母语“泰语”定义为自然语言,因此挑战在于如何应用最初为英语设计的NLP概念。我们从标记化开始,从泰国首席投诉中提取泰国令牌,然后对令牌进行分析,以便根据ICD-10代码分配特定的标签。
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Signs and Symptoms Tagging for Thai Chief Complaints Based on ICD-10
This paper presents a natural language processing (NLP) approach to construct signs and symptoms corpus in order to identify signs and symptoms recoded in a Thai chief complains (CCs) based on the International Statistical Classification of Diseases and Related Health Problems 10th Revision (ICD-10) form. We define our native language "Thai language" as the natural language in our works thus the challenge is how to apply NLP concept that is originally designed for English language. We start from tokenization to extract Thai token from Thai chief complains, and then the tokens is analyzed in order to assigning a specific tag in terms of ICD-10 code.
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