ISPO: An Integrated Ontology of Symptom Phenotypes for Semantic Integration of Traditional Chinese Medical Data
Zixin Shu, Rui Hua, Dengying Yan, Chenxia Lu, Ning Xu, Jun Li, Hui, Zhu, Jia Zhang, Dan Zhao, Chenyang Hui, Junqiu Ye, Chu Liao, Qi Hao, Wen Ye,, Cheng Luo, Xinyan Wang, Chuang Cheng, Xiaodong Li, Baoyan Liu, Xiaji Zhou,, Runshun Zhang, Min Xu, Xuezhong Zhou

TL;DR
This paper presents ISPO, an integrated ontology of symptom phenotypes for Traditional Chinese Medicine, enabling semantic interoperability and improved data analysis of Chinese medical records through comprehensive annotation and mapping.
Contribution
The study constructs ISPO, a novel comprehensive ontology integrating TCM symptom data with biomedical vocabularies, enhancing semantic interoperability and clinical data analysis capabilities.
Findings
ISPO covers 3,147 concepts and 23,475 terms.
Achieves over 95% coverage in clinical datasets.
Supports effective mapping of clinical terms to ontologies.
Abstract
Symptom phenotypes are one of the key types of manifestations for diagnosis and treatment of various disease conditions. However, the diversity of symptom terminologies is one of the major obstacles hindering the analysis and knowledge sharing of various types of symptom-related medical data particularly in the fields of Traditional Chinese Medicine (TCM). Objective: This study aimed to construct an Integrated Ontology of symptom phenotypes (ISPO) to support the data mining of Chinese EMRs and real-world study in TCM field. Methods: To construct an integrated ontology of symptom phenotypes (ISPO), we manually annotated classical TCM textbooks and large-scale Chinese electronic medical records (EMRs) to collect symptom terms with support from a medical text annotation system. Furthermore, to facilitate the semantic interoperability between different terminologies, we incorporated public…
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Taxonomy
TopicsTraditional Chinese Medicine Studies · Biomedical Text Mining and Ontologies
MethodsOntology
