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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

  1. Submit an authorized clinical PDF/image, OCR its text, and retain source pages. [src10-strands-normalize-medical-documents-to-standard-codes]
  2. Extract diagnoses, medications, treatments, patient details, and vitals into structured JSON fields. [src10-strands-normalize-medical-documents-to-standard-codes]
  3. 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

Permissions

Limitations

Code mapping assists coding; it is not diagnosis or treatment advice and requires qualified clinical/coding review.

Pinned upstream source

https://github.com/strands-agents/samples/blob/bd46f959844424a9544133e1263c8eae61e7fe9b/python/04-industry-use-cases/healthcare/medical-document-processing-assistant/README.md

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

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License: Apache-2.0

Main topic

Turn ecommerce campaign materials into a reviewable weekly brief

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