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Article

Beyond Identifier Matching: An Empirical Characterization of Failure Modes in Biomedical Knowledge Graph Integration

2026-05-28

Abstract excerpt

<h4>Objective</h4> Biomedical knowledge graphs (KGs) such as PrimeKG, Hetionet, UMLS, and PharmGKB are increasingly used as the substrate for downstream machine-learning, retrieval-augmented generation, drug-repurposing, and electronic health record (EHR) augmentation pipelines. The dominant assumption in published work is that integrating two or more such KGs is a tractable engineering step solved by identifier...

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Literature Corpus work
b782a965-77e9-507e-ae8b-3c1183edc1be
DOI
10.64898/2026.05.26.26354182
Open publication

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Beyond Identifier Matching: An Empirical Characterization of Failure Modes in Biomedical Knowledge Graph IntegrationDOI 10.64898/2026.05.26.26354182
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