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Extract medical documents and map standard codes
Extract clinical facts from PDFs or images, produce structured JSON, and map ICD-10, RxNorm, and SNOMED CT codes.
Goal
Turn unstructured clinical documents into reviewable coded records rather than a free-text summary.
Steps
- Submit an authorized clinical PDF/image, OCR its text, and retain source pages. [src10-strands-normalize-medical-documents-to-standard-codes]
- Extract diagnoses, medications, treatments, patient details, and vitals into structured JSON fields. [src10-strands-normalize-medical-documents-to-standard-codes]
- Map ICD-10, RxNorm, and SNOMED CT separately; flag low-confidence or unmapped items for human review. [src10-strands-normalize-medical-documents-to-standard-codes]
How to verify
Check each code against its source page and term; unknown terms should remain unmapped rather than receive invented codes.
Troubleshooting
For OCR errors in dose or units, inspect the source page and flag review; for code-version mismatches, update the terminology source and retry that field.
Permissions
Prerequisites
- Python sample dependencies, authorized non-real clinical PDFs/images, and terminology-code versions.
Permissions
- Document uploads go to the configured model/OCR services; documents may contain health information, so use synthetic or explicitly authorized data only.
Limitations
Code mapping assists coding; it is not diagnosis or treatment advice and requires qualified clinical/coding review.
Pinned upstream source
- Repository
- strands-agents/samples
- File path
- python/04-industry-use-cases/healthcare/medical-document-processing-assistant/README.md
- Pinned commit
bd46f959844424a9544133e1263c8eae61e7fe9b- Source checked
- 2026-10-14 · Reviewed against the pinned upstream source
Repository metrics
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License: Apache-2.0
Main topic
Turn ecommerce campaign materials into a reviewable weekly brief