clinical-agent-skills

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.

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.

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.

Generates possible diagnostic hypotheses based on clinical text, including symptoms, findings, and test results. Use when analyzing patient data to assist clinical reasoning and suggest differential diagnoses.

Summarizes clinical text into a structured medical summary using formats such as SOAP (Subjective, Objective, Assessment, Plan). Use when condensing patient records, clinical notes, or medical histories into concise, structured summaries.

Extracts structured clinical entities such as diseases, symptoms, medications, procedures, and lab results from clinical text. Use when analyzing medical notes, patient records, or extracting structured information from unstructured healthcare data.

Anonymizes clinical text by removing or replacing personally identifiable information (PHI/PII) such as names, dates, locations, identifiers, and contact details. Use when processing clinical notes, patient records, or any sensitive healthcare data.