Construction of Knowledge Graph Based on Literature Data by Taking Treatment of Diabetic Peripheral Neuropathy with Traditional Chinese Medicine as An Example
10.13422/j.cnki.syfjx.20231448
- VernacularTitle:基于文献数据的知识图谱构建——以中医药治疗糖尿病周围神经病变为例
- Author:
Jiaqi CHAI
1
;
Yumeng TAN
1
;
Xinghua XIANG
1
;
Miaomiao LI
1
;
Tiancai WEN
2
;
Hui ZHAO
1
Author Information
1. Institute of Basic Research in Clinical Medicine，China Academy of Chinese Medical Sciences， Beijing 100700，China
2. TCM Data Center，China Academy of Chinese Medical Sciences，Beijing 100700，China
- Publication Type:Journal Article
- Keywords:
traditional Chinese medicine;
diabetic peripheral neuropathy（DPN）;
knowledge graph;
Neo4j;
syndrome elements;
syndrome types;
treatment method and principle
- From:
Chinese Journal of Experimental Traditional Medical Formulae
2024;30(6):144-150
- CountryChina
- Language:Chinese
-
Abstract:
ObjectiveTo systematically sort out the knowledge framework and conceptual logic relationship of "disease-syndrome-treatment-prescription-medicine" in the existing literature on traditional Chinese medicine（TCM） treatment of diabetic peripheral neuropathy（DPN）， to construct of the knowledge map of TCM treatment of DPN， and to promote the explicitation of the implicit knowledge in the literature on the treatment of DPN with TCM. MethodTaking the literature of China National Knowledge Infrastructure about TCM treatment of DPN as the main data source， TCM-related concepts and entities were constructed by manual citation， and the corresponding relationships between the entities were established. Structured data were formed by processing with Python 3.7， and the knowledge graph was constructed based on Neo4j 3.5.34 graph database. ResultThe resulting knowledge graph with TCM diagnosis and treatment logic， defined 12 node labels such as prescriptions， Chinese medicines and syndrome types at the schema layer， as well as 4 types of relationships， such as inclusion， correspondence， selection and composition. It could support the query and discovery of nodes（syndrome elements， syndrome types and treatment methods）， as well as the relationship between each node. ConclusionBased on the literature data， this study constructed a knowledge map for TCM treatment of DPN， which brought together various methods of TCM treatment of DPN， including internal and external treatment. The whole chain knowledge structure of syndrome differentiation and classification for DPN treatment is formed from syndrome element analysis， syndrome type composition to treatment method selection， which can provide new ideas and methods for literature data to serve clinical and scientific research work， as well as reference for visualization of TCM literature knowledge， intellectualization of TCM knowledge services and the standardization of TCM diagnosis and treatment.
