Combining Clinical Data and Domain Knowledge for Analyzing Mental Disorder Concept Relatedness and Usage

Concept relatedness played a significant role in biomedical domain as it facilitates a number of tasks including information extraction, natural language processing, concept clustering and classification. In this research, we leveraged concept embedding to measure concept relatedness and compared concept relatedness based on embedding to the Gold standard concept classification. We also used real-world data from mental health domain to measure concept usage. The results revealed that compatibility accuracy measure F score was 0.21 and about 20% of SNOMED Mental Disorder concepts are utilized for patient cohort selection task. This study contributed a method for exploring concept relatedness and usage, and different approaches to medical concept classification, providing insights for medical ontology developers and domain experts.