摘要
对疾病进行编码是将疾病诊断名称转化为标准ICD(国际疾病分类)编码的过程.鉴于编码量庞大和人工编码效率低等原因,有必要实现疾病编码的自动化.提出一种自动化的疾病编码方法,使用一种文本建模方法将ICD表示为文本集,然后借助文本相关性度量,获取与待编码疾病诊断名称最相关的ICD编码.经实验验证,本文提出的自动化疾病编码方法准确率较高、效率优秀、分类层次变换灵活,可广泛应用于各种类型的数据分析场景.
Disease coding is the process of transforming diagnosis names to standard ICD（International Classification of Diseases） codes. Due to the huge amount of workload and the low efficiency of manual coding, it＇s necessary to achieve the automation of disease coding. This paper presents a method for automated coding of disease. Specifically, we present ICD as documents with a text modeling approach, and then get the most relevant ICD code of a diagnosis name with the text correlation measure. The experiments proves that our method has a good accuracy, it＇s very efficient and easy to switched among classification levels, could be widely applied to various types of data analysis scenarios.
出处
《计算机系统应用》
2015年第12期265-268,共4页
Computer Systems & Applications
基金
高等学校博士学科点专项科研基金新教师类资助课题(20113402120026)
安徽省自然科学基金(1208085QF112)
安徽省高等学校优秀青年人才基金(2012SQRL001ZD)
中央高校基本科研业务费专项资金(WK2101020004
WK0110000007)
