基于组合语义相似度计算的疾病术语自动编码

Automatic Coding Method for Disease Term Based on Combined Semantic Similarity Calculation

当前国内医疗机构疾病编码主要采用国际疾病分类ICD-10标准并由人工完成,人工工作量大、时间成本高。提出了一种基于组合语义相似度技术进行疾病术语自动编码的方法,其基于领域知识库结合分词、实体识别和词向量表示技术进行术语相似度计算。通过在妇产科疾病中的应用表明,该方法在术语自动编码精度能达到80%以上,可以有效辅助临床医生书写诊断编码,减少病案科审核工作量,提升总体工作效率。

Currently, the national medical institutions mainly adopt the ICD-10 standard for the disease code,and it iscompleted manually. The large amount of manual work and time cost are the main problems that we are facing. This paper proposes an automatic coding disease terms methodbased on domain knowledge, entity recognition and Word2 vec technology for term similarity calculation. The application in the digestive diseases shows that the method can achieve more than 80% accuracy in the term automatic coding, which can effectively assist the clinician to write the diagnosis code, reduce the workload of the medical record review, and improve the overall work efficiency.