L’interface est localisée ; les présentations et documents des Skills sont traduits automatiquement par IA dans votre langue. Le code, les commandes, chemins et termes techniques restent en version originale, et le document de l’auteur fait foi.
Explorer les Skills
Développement · SKILL.md

clinical-extraction-grounding

clinical-extraction-grounding

Route clinical NER, section/context, grounding, and codeable-concept workflows.

Independent GitHub snapshot · Automated classification · Original documentation governs

Documentation de la Skill

GitHub

name: clinical-extraction-grounding description: "Route clinical NER, section/context, grounding, and codeable-concept workflows." disable-model-invocation: true metadata: disco-role: operating license: Apache 2.0

Clinical extraction and grounding

Use this sub-skill for local-first clinical and biomedical span extraction, section-aware context, offline terminology grounding, problem/medication/lab helpers, and codeable-concept-style outputs.

Use when

  • You need openmed.analyze_text for clinical or biomedical NER.
  • You need note routing, section detection, or assertion axes.
  • You need local vocabulary grounding and codeable-concept previews.
  • You need zero-shot label-map guidance from openmed.ner.

Route away

  • PII or PHI redaction, de-identification, or re-identification -> route to the de-identification sub-skill.
  • REST, MCP, service deployment, or endpoint wiring -> route to the interoperability-serving sub-skill.
  • Model download, cache, backend conversion, or mobile runtime packaging -> route to the model-runtimes-mobile sub-skill.
  • Table release-risk or audit/compliance workflows -> route to the structured-risk-evaluation sub-skill.

Bundled assets

  • references/api-reference.md
  • references/clinical-workflows.md
  • references/troubleshooting.md
  • scripts/clinical_fixture_pipeline.py

Fast path

  1. Read the workflow notes.
  2. Run the bundled fixture script for an offline smoke check.
  3. Use the API reference for exact public calls and payload shapes.

Output contract

Keep all examples synthetic. Use local-only loaders and caller-owned vocabulary snapshots. Do not require network fetches, remote model downloads, or restricted terminology bundles.

For a complete end-to-end draft, use the bundled references and script.

Skills enregistrées