A framework for normalized extraction of fine-grained traditional Chinese medicine symptom entities and relations.

ABSTRACT:

Background

In Traditional Chinese Medicine Electronic Medical Records (TCM EMRs), symptom descriptions are often semi-structured, and coarse-grained annotation can lead to symptom nesting and information loss. To address these limitations and improve the precision of symptom representation, this study proposes a fine-grained symptom entity annotation system. Its objective is to convert unstandardized symptom expressions into structured data, thereby enhancing the correlation and standardization of symptom information to support intelligent TCM diagnosis and treatment.

Methods

A five-step approach was employed: First, we drafted a fine-grained annotation guideline based on existing research. Second, we annotated symptom entities and iteratively refined the annotations through

SUBMITTER: Gou X 

PROVIDER: S-EPMC12683873 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature