Industry · Medical Devices
Medical Devices
Build MDR/IVDR-oriented literature reviews and clinical evaluation evidence with inspectable include/exclude trails and standardized reporting.
The challenge
Device evidence packages must show what entered the corpus, why studies were included or excluded, and how humans intervened. Predicates, intended use, and performance endpoints leave little room for opaque tools or undocumented spreadsheet screening.
How LRN works here
A workflow your team can defend
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01
Gather the corpus
Versioned search strings and multi-source intake with deduplication and timestamps for lineage.
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02
Generate analyses
Explainable AI classification with performance metrics and SME gates on edge records.
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03
Build the audit trail
AI Package Insert sections: data lineage, model rationale, human review, compliance-oriented outputs.
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04
Review & package
Completeness checks and export-ready reports for clinical evaluation and post-market updates.
What you leave with
CER / PER support
Structured literature paths aligned to evaluation narratives.
Inspectable decisions
Every exclude can leave a reason for internal and external review.
Living updates
Refresh the corpus without rebuilding the method from scratch.
Next step
Talk with us about LRN for medical devices.