  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
available biomedical vocabularies by manual mapping between Chinese terms and
English terms with cross-references to source vocabularies. In addition, we
evaluated the ISPO using independent clinical EMRs to provide a high-usable
medical ontology for clinical data analysis. Results: By integrating 78,696
inpatient cases of EMRs, 5 biomedical vocabularies, 21 TCM books and
dictionaries, ISPO provides 3,147 concepts, 23,475 terms, and 55,552 definition
or contextual texts. Adhering to the taxonomical structure of the related
anatomical systems of symptom phenotypes, ISPO provides 12 top-level categories
and 79 middle-level sub-categories. The validation of data analysis showed the
ISPO has a coverage rate of 95.35%, 98.53% and 92.66% for symptom terms with
occurrence rates of 0.5% in additional three independent curated clinical
datasets, which can demonstrate the significant value of ISPO in mapping
clinical terms to ontologies.
