Bridging Bibliometrics and Biology: A Framework for the Relevance Scoring and Biological Stratification of Scalable MeSH Co-occurrence Networks

A MeSH co-occurrence network seeded on Allergic Contact Dermatitis recovers key event terminology and identifies highly specific literature overlooked by standard retrieval, using Symmetrically normalized Article Relevancy Scores.

• Why it matters: Rigid search strings in systematic reviews can miss non-obvious but relevant topics, and MeSH term relationships and relevance to a hypothesis are rarely made explicit.
• What they did: The method extracts and networks MeSH terms from MEDLINE, prunes the co-occurrence graph via an unsupervised consensus of Metropolis-criterion likelihood searches, then computes ARS with publication-volume bias correction and maps terms via Mean Relevancy Scoring.
• The result: Benchmarking against the expert-curated Adverse Outcome Pathway for Allergic Contact Dermatitis shows the framework can quantitatively assess associated MeSH terminology and extract biologically relevant concepts and relationships for review and pathway mapping.

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