concept-mapping-ai
CommunityMap clinical concepts to OMOP with confidence.
AuthorBorisDelange
Version1.0.0
Installs0
System Documentation
What problem does it solve?
It reduces the manual effort and inconsistency of mapping source clinical concepts (measurements, conditions, procedures, observations) to the correct OMOP standard concepts by generating candidate matches and providing structured reasoning.
Core Features & Use Cases
- Agentic OMOP Concept Mapping: Produces ranked candidates for each source concept using DuckDB search, precomputed similarity scores, and clinical reasoning.
- SSSOM-graded Equivalence: Assigns equivalence levels (skos:exactMatch, closeMatch, broadMatch, narrowMatch, relatedMatch) with evidence-oriented comments to support reviewer decisions.
- Two Write Destinations: Saves results either as UI-reviewable suggestions in
similarity-scores.parquetor as reviewer-confirmed authored mappings inmappings.json. - Batch Processing with Guardrails: Operates on prepared DuckDB session context, supports per-batch review modes, and handles edge cases like missing matches or non-standard concepts.
Quick Start
Ask the concept-mapping orchestrator to run the concept-mapping-ai skill for your selected source concept batch with an existing DuckDB session context and a chosen destination mode (suggestions or mappings).
Dependency Matrix
Required Modules
None requiredComponents
references
💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: concept-mapping-ai Download link: https://github.com/BorisDelange/Linkr/archive/main.zip#concept-mapping-ai Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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