菜单
Query the PsyTAR psychiatric adverse-reaction corpus. Use when the user asks about patient-reported ADRs, withdrawal symptoms, drug indications, or effectiveness for Zoloft, Lexapro, Cymbalta, or Effexor XR. Accepts drug names (brand or generic), symptom terms, or UMLS CUIs.
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
基于 SOC 职业分类
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| name | psytar-query |
| description | Query the PsyTAR psychiatric adverse-reaction corpus. Use when the user asks about patient-reported ADRs, withdrawal symptoms, drug indications, or effectiveness for Zoloft, Lexapro, Cymbalta, or Effexor XR. Accepts drug names (brand or generic), symptom terms, or UMLS CUIs. |
891 patient reviews → 6 009 annotated sentences → extracted ADR / WD / SSI / DI entities → mapped to 918 UMLS + 755 SNOMED CT concepts.
| Input Pattern | Detected As | Targets |
|---|---|---|
C0917801 | UMLS CUI | *_Mapped sheets only (UMLS1/UMLS2 cols) |
Zoloft / sertraline | Drug name | drug_id or drug columns (alias-aware) |
nausea, insomnia … | Free text | substring across all cell values |
Generic ↔ brand aliases: sertraline↔Zoloft, escitalopram↔Lexapro, duloxetine↔Cymbalta, venlafaxine↔Effexor.
| Function | Input | Returns |
|---|---|---|
search(entity, sheet?, label?) | single string | {sheet: [row_dict]} |
search_batch(entities, sheet?, label?) | list of strings | {entity: {sheet: [row_dict]}} |
summarize(results, entity) | result dict + label | compact text |
to_json(results) | result dict | list[dict] (flat, adds _sheet) |
describe() | — | dataset overview text |
sheet — restrict to one sheet (fuzzy-matched: "ADR" → ADR_Identified).label — when on Sentence_Labeling, keep only rows where the named
label column (ADR / WD / EF / INF / SSI / DI) equals 1.| Sheet | Description | Key Columns |
|---|---|---|
Sample | Original posts | drug_id, rating, indication, side-effect, comment, gender, age, duration |
Sentence_Labeling | 6 009 sentences, binary labels | drug_id, sentence_index, sentences, ADR, WD, EF, INF, SSI, DI, Findings, others, rating, category |
ADR_Identified | Extracted ADR mentions | drug_id, sentence_index, sentences, ADR1 … ADRn |
WD_Identified | Extracted WD mentions | drug_id, sentence_index, sentences, WD1 … WDn |
SSI_Identified | Extracted SSI mentions | drug_id, sentence_index, sentences, SSI1 … SSIn |
DI_Identified | Extracted DI mentions | drug_id, sentence_index, sentences, DI1 … DIn |
ADR_Mapped | ADR → UMLS/SNOMED | drug_id, sentence_index, ADR/ADRs, UMLS1, UMLS2, SNOMED-CT, mild, moderate, severe, persistent, not-persistent, body-site, rating, drug, class, type, entity_type |
WD_Mapped | WD → UMLS/SNOMED | (same structure as ADR_Mapped) |
SSI_Mapped | SSI → UMLS/SNOMED | (same structure) |
DI_Mapped | DI → UMLS/SNOMED | (same structure) |
mild, moderate, severe — severity descriptors;
persistent, not-persistent — duration; body-site — anatomical site;
entity_type — Cognitive / Physiological / Psychological / Functional.
from importlib.machinery import SourceFileLoader
m = SourceFileLoader("psytar", "36_PSYTAR.py").load_module()
# overview
print(m.describe())
# drug → ADR mappings
res = m.search("Zoloft", sheet="ADR_Mapped")
print(m.summarize(res, "Zoloft"))
# generic name works too
res = m.search("sertraline", sheet="ADR_Mapped")
# symptom in one Identified sheet
res = m.search("nausea", sheet="ADR_Identified")
# symptom across all sheets
res = m.search("insomnia")
# UMLS CUI (auto-scoped to Mapped sheets)
res = m.search("C0917801")
# withdrawal sentences for Effexor
res = m.search("Effexor", sheet="Sentence_Labeling", label="WD")
# batch
batch = m.search_batch(["Lexapro", "insomnia", "C0917801"])
# JSON for pipeline
flat = m.to_json(m.search("Cymbalta"))
PsyTAR_dataset.xlsx — set via DATA_PATH or env PSYTAR_XLSX