extract-clinical-entities-to-fhir
仓库创建 2025年10月4日最近提交 3 小时前SkillHot 收录 3 小时前
▸ 精选理由
适合将本地NER结果转换成标准FHIR包以便集成与审计。
▸ 风险提示
处理真实临床文本时需注意PHI与合规性。
这个 Skill 做什么
把OpenMed抽取的临床实体映射为确定性的FHIR R4资源与Bundle。
把 OpenMed 从文本里抽出的临床实体翻成确定性的 FHIR R4 资源和一个 Bundle,方便一键上报到 EHR 或下游系统。适用于把本地或已脱敏的 NER 输出变成 Conditions、MedicationStatement、Observation 等标准资源时使用。输出可重复、结构化,不会凭空发明术语编码。
▸ 展开 SKILL.md 英文原文
Extract clinical entities from synthetic or already de-identified text with OpenMed and map them into deterministic FHIR R4 resources and a Bundle. Use when an agent must turn local clinical NER output into Conditions, MedicationStatements, Observations, or other FHIR resources without inventing terminology codes.
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给你的 Agent 一句话(通用)
帮我安装这个 skill:https://raw.githubusercontent.com/maziyarpanahi/openmed/master/skills/extract-clinical-entities-to-fhir/SKILL.md或 curl 直取 SKILL.md
curl -fsSL "https://raw.githubusercontent.com/maziyarpanahi/openmed/master/skills/extract-clinical-entities-to-fhir/SKILL.md"SKILL.MD 节选查看完整文件 ↗
# Extract clinical entities to FHIR Separate extraction from clinical coding. OpenMed finds spans and supplies the mechanical FHIR builders; the application decides which resource type and status are clinically appropriate. ## Procedure 1. Keep the source synthetic, or de-identify it inside the trusted boundary before extraction. 2. Run `openmed.analyze_text` with the task-appropriate clinical model. 3. Filter predictions by label and confidence; preserve offsets in a PHI-safe audit record. 4. Map each accepted span to the correct FHIR resource type. 5. Add terminology codes only from a user-approved mapping or terminology service. Never invent a code. 6. Assemble resources with
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