From keywords to knowledge: How IMO Health’s terminology maximizes relevant PubMed evidence
Authors
Liang-Chin Huang, PhD Principal NLP Scientist IMO Health
Kyeryoung Lee, PhD Senior Principal Biomedical Engineer IMO Health
Systematic literature reviews (SLRs) shape regulatory submissions and portfolio decisions. But those decisions are only as strong as the evidence behind them.
Even experienced teams using keywords, MeSH, or AI–driven query expansion can miss relevant studies – especially for complex clinical questions. And in life sciences, incomplete evidence isn’t just inefficient. It introduces real risk.
In this white paper, we examine where traditional PubMed workflows fall short and share new performance data showing how grounding AI in expert-curated clinical terminology:
Retrieves more objective-relevant studies
Reduces manual trial–and–error search refinement
Improves consistency and auditability across SLR workflows
Download the white paper to see how terminology-grounded AI strengthens evidence from the start.
Featured speaker(s)
April Curtis
Marketing Director
IMO
Thomas Magnum
Marketing Manager
IMO
B.A. Baracus
Data Analyst
IMO
B.A. Baracus
Data Analyst
IMO
Who It's For
Download the white paper
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