Abstract:

Chinese medicine often uses natural language to describe the symptoms of the disease, which leads to inconsistent naming of the symptoms and affects the results of data mining analysis and clinical efficacy evaluation. Based on the diagnosis and treatment data of clinical special diseases of a famous Chinese medicine practitioner, this study explored on how to standardize the terminology in clinical diagnosis and treatment data. From the perspective of semantic analysis of standardization symptoms terms, we introduced the concept of the term properties and the relationships between terms in the process of establishing the preferred terms, and solved the problem of multi-word meaning and polysemy between symptoms. Also, we sorted out the disease diagnosis terms according to the ICD-11 Chinese version, standardized the names of traditional Chinese medicines according to Chinese Pharmacopoeia, and sorted the curative effect evaluation terms according to “cure”, “improvement”, and “unhealed”. We finally obtained 558 symptom terms, among which 164 were preferred terms, and obtained 394 synonymous terms, 23 diagnosis terms, 21 terms of efficacy evaluation. The standardized data can be used for data mining analysis.

Key words: epilepsy diagnosis and treatment data, data standardization, preferred term, synonymous term, term properties