BSO-AD: An Ontology for Representing and Harmonizing Behavioral Social Knowledge in ADRD

Objective: RD (BSO-AD) to represent and integrate BSFs with respect to ADRD. Material and Methods: BSO-AD was developed following established ontology design principles, prioritizing reuse of existing ontology elements to ensure semantic interoperability. It was built upon the Social Determinants of Health Ontology (SDoHO) and the Drug-Repurposing Oriented Alzheimer's Disease Ontology (DROADO). BSF-related classes were enriched with ICD-10-CMZ55-Z65 codes and ADRD-related classes with AD-Onto. Relationships between BSFs and ADRD were derived through literature mining. Ontology quality was evaluated through Hootation-based expert review and an LLM-assisted framework assessing structural coverage and semantic coherence. Results: BSO-AD contains 2,275 classes, 153 object properties, and 49 data properties. Expert review demonstrated strong rational agreement (0.95), with disagreements resolved through discussion. LLM-based evaluation showed high category coverage rates (≥ 0.97) and robust semantic alignment with the relevant literature (average completeness = 0.79; conciseness = 0.94). Discussion and Conclusion: BSO-AD is, to our knowledge, the first ontology to systematically represent BSFs and hierarchically model their interrelationships in ADRD. It establishes a semantic backbone for computational analysis and knowledge integration. The LLM-assisted evaluation framework demonstrates the feasibility of scalable, automated ontology assessment.

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Publication Details

Journal
medRxiv
Published
2026-03-31
DOI
https://doi.org/10.64898/2026.03.30.26349756
Primary Topic
Biomedical Text Mining and Ontologies
Type
article
Field-Weighted Citation Impact
0.00

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article

BSO-AD: An Ontology for Representing and Harmonizing Behavioral Social Knowledge in ADRD

Avanti Bhandarkar, Yutong Hu, Na Zhao, Cui Tao et al.
medRxiv
Biomedical Text Mining and Ontologies
article

BSO-AD: An Ontology for Representing and Harmonizing Behavioral Social Knowledge in ADRD

Avanti Bhandarkar, Yutong Hu, Na Zhao, Cui Tao, FANG LI, Rakesh Kumar, Haifang Li, Weiguo Cao, Isaac Heath Clark, Yue Yu
article en

Abstract

Objective: RD (BSO-AD) to represent and integrate BSFs with respect to ADRD. Material and Methods: BSO-AD was developed following established ontology design principles, prioritizing reuse of existing ontology elements to ensure semantic interoperability. It was built upon the Social Determinants of Health Ontology (SDoHO) and the Drug-Repurposing Oriented Alzheimer's Disease Ontology (DROADO). BSF-related classes were enriched with ICD-10-CMZ55-Z65 codes and ADRD-related classes with AD-Onto. Relationships between BSFs and ADRD were derived through literature mining. Ontology quality was evaluated through Hootation-based expert review and an LLM-assisted framework assessing structural coverage and semantic coherence. Results: BSO-AD contains 2,275 classes, 153 object properties, and 49 data properties. Expert review demonstrated strong rational agreement (0.95), with disagreements resolved through discussion. LLM-based evaluation showed high category coverage rates (≥ 0.97) and robust semantic alignment with the relevant literature (average completeness = 0.79; conciseness = 0.94). Discussion and Conclusion: BSO-AD is, to our knowledge, the first ontology to systematically represent BSFs and hierarchically model their interrelationships in ADRD. It establishes a semantic backbone for computational analysis and knowledge integration. The LLM-assisted evaluation framework demonstrates the feasibility of scalable, automated ontology assessment.

medRxiv
Emory University (US), Mayo Clinic in Florida (US)
National Institute of Mental Health
Openalex Percentile: Top 30%
Biomedical Text Mining and Ontologies
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