# Cadec Query

> Query the CADEC (CSIRO Adverse Drug Event Corpus). Use whenever the user asks about adverse drug event mentions in consumer health text, entity annotations from patient forum posts, MedDRA/SNOMED-CT normalised ADR spans, or wants to look up drugs, symptoms, or coded entities in the CADEC corpus.

- Skill: `gabrielmoreira/cadec-query` (Agent Skill, multi-file: 6 files)
- Install (CLI): `npx skillmds@latest add gabrielmoreira/cadec-query`
- Raw SKILL.md: https://api.skillmd.com/api/skills/gabrielmoreira/cadec-query/raw
- Safety review: pending (external: skill-scanner PASS, skillspector PASS)
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: AI & ML
- Author: gabrielmoreira (https://skillmd.com/u/gabrielmoreira)
- Updated: 2026-09-09
- Page: https://skillmd.com/skills/gabrielmoreira/cadec-query

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# CADEC Query Skill

Search CADEC annotated patient forum posts by any entity. Auto-detects type:

| Input Pattern | Detected As | Match Logic |
|---|---|---|
| `10019211` (8 digits) | MedDRA code | exact on normalizations.code |
| `22253000` (6-18 digits) | SNOMED CT code | exact on normalizations.code |
| anything else | free text | substring on entity text, type, or doc_id |

## API

| Function | Input | Returns |
|---|---|---|
| `load_cadec(path)` | JSON path | list[dict] (cached) |
| `search(entity)` | single entity string | list[dict] |
| `search_batch(entities)` | list of entity strings | dict[str, list[dict]] |
| `summarize(hits, entity)` | hits + label | compact text |
| `to_json(hits)` | list[dict] | same list (JSON-ready) |

## Entity Types in Corpus

| Type | Description |
|---|---|
| ADR | Adverse Drug Reaction |
| Drug | Medication mention |
| Disease | Pre-existing condition |
| Symptom | Patient-reported symptom |
| Finding | Clinical finding |

## Usage

See `if __name__ == "__main__"` block in `34_CADEC.py` for runnable examples:
drug name search, ADR text search, MedDRA code lookup, batch search, JSON output.

## Data

- **Source**: CADEC v2, CSIRO (AskaPatient.com forum posts)
- **Local file**: `cadec_combined.json` built from BRAT `.txt` + `.ann` files
- **Annotations**: Original spans + MedDRA + SNOMED CT normalisations
- **Stats**: ~1,250 documents, ~7,600 entity annotations
- **Path**: `DATA_PATH` variable in `34_CADEC.py`
- **Citation**: Karimi et al., 2015. *J Biomed Inform* 55:73–81