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Answers questions based strictly on clinical text, such as patient records or medical notes. Use when extracting specific information from clinical documents in a reliable and grounded manner.
Codex または Claude でインストール この Prompt をコピーして Codex、Claude、または他のアシスタントに貼り付けると、Skill ページを確認してインストールできます。
SOC 職業分類に基づく
Classifies clinical text into predefined categories such as severity, urgency, or clinical type based on patient information. Use when assigning labels for triage, prioritization, or categorization of medical cases.
Extracts and organizes clinical events into a chronological timeline based on patient records or medical notes. Use when reconstructing the sequence of symptoms, diagnoses, treatments, or hospital events.
Converts unstructured clinical text into structured JSON by extracting key medical information such as symptoms, diagnoses, medications, procedures, and temporal data. Use when transforming clinical notes into machine-readable format.
Generates structured clinical reports (e.g., discharge summaries, medical reports, or clinical notes) based on patient data. Use when transforming clinical information into clear, standardized medical documentation.
Assesses patient risk level (e.g., low, medium, high) based on clinical information such as symptoms, history, and findings. Use when evaluating potential severity, complications, or need for prioritization in clinical contexts.
Maps clinical text to standardized diagnosis codes (e.g., ICD-10) based on explicitly mentioned conditions. Use when extracting or assigning diagnostic codes from medical records, clinical notes, or patient summaries.
| name | clinical-question-answering |
| description | Answers questions based strictly on clinical text, such as patient records or medical notes. Use when extracting specific information from clinical documents in a reliable and grounded manner. |
When answering clinical questions, follow these steps:
Do not infer or assume missing details.
If the answer is not present in the text:
Do not guess or hallucinate.
If appropriate, include a short excerpt from the text that supports the answer.
Return the result as structured text:
Answer: ...
Evidence: ...
If no evidence is available:
Answer: Not available in the provided text.