Skip to main content

Extract structured data from medical documents with Google Gemini AI

Workflow preview

Workflow preview
100%
Extract structured data from medical documents with Google Gemini AI preview
Open on n8n.io

Important notice

This workflow is provided as-is. Please review and test before using in production.

1. Workflow Overview

How it works Transform medical documents into structured data using Google Gemini AI with enterprise grade accuracy. Classifies document types (receipts, prescriptions, lab reports, clinical notes)...

Best for

  • Document Extraction automation workflows
  • AI Summarization automation workflows
  • advanced n8n builders looking for reusable templates

Tools used

n8n-nodes-base.stickynote, n8n-nodes-base.webhook, n8n-nodes-base.set, n8n-nodes-base.httprequest, n8n-nodes-base.extractfromfile, n8n-nodes-base.respondtowebhook

Source and attribution

This workflow is cataloged by N8N Workflows and links back to its original n8n.io source page by Louis Chan.

Original n8n.io source

1.1 Workflow description

Title
Extract structured data from medical documents with Google Gemini AI
Workflow name
Extract structured data from medical documents with Google Gemini AI

How it works

Transform medical documents into structured data using Google Gemini AI with enterprise-grade accuracy.

Classifies document types (receipts, prescriptions, lab reports, clinical notes)

  • Extracts text with 95%+ accuracy using advanced OCR
  • Structures data according to medical taxonomy standards
  • Supports multiple languages (English, Chinese, auto-detect)
  • Tracks processing costs and quality metrics automatically

Set up steps

Prerequisites

Google Gemini API key (get from Google AI Studio)

Quick setup

  1. Import this workflow template
  2. Configure Google Gemini API credentials in n8n
  3. Test with a sample medical document URL
  4. Deploy your webhook endpoint

Usage

Send POST request to your webhook:

{
  "image_url": "https://example.com/medical-receipt.jpg",
  "expected_type": "financial",
  "language_hint": "auto"
}
Get structured response:
json{
  "success": true,
  "result": {
    "documentType": "financial",
    "metadata": {
      "providerName": "Dr. Smith Clinic",
      "createdDate": "2025-01-06",
      "currency": "USD"
    },
    "content": {
      "amount": 150.00,
      "services": [...]
    },
    "quality_metrics": {
      "overall_confidence": 0.95
    }
  }
}

Use cases

Healthcare Organizations

  • Medical billing automation - Process receipts and invoices automatically
  • Insurance claim processing - Extract data from claim documents
  • Clinical documentation - Digitize patient records and notes
  • Data standardization - Consistent structured output format

System Integrators

  • EMR integration - Connect with existing healthcare systems
  • Workflow automation - Reduce manual data entry by 90%
  • Multi-language support - Handle international medical documents
  • Quality assurance - Built-in confidence scoring and validation

Supported Document Types

  • Financial: Medical receipts, bills, insurance claims, invoices
  • Clinical: Medical charts, progress notes, consultation reports
  • Prescription: Prescriptions, medication lists, pharmacy records
  • Administrative: Referrals, authorizations, patient registration
  • Diagnostic: Lab reports, test results, screening reports
  • Legal: Medical certificates, documentation forms

1.2 Logical Blocks

This catalog entry is organized from the workflow JSON. The node-level section below shows the executable blocks available for review before importing the template.

2. Block-by-Block Analysis

Block 1 - Sticky Note

Type / Role
n8n-nodes-base.stickyNote - stickyNote
Config choices
Version 1

Block 2 - Sticky Note1

Type / Role
n8n-nodes-base.stickyNote - stickyNote
Config choices
Version 1

Block 3 - Sticky Note3

Type / Role
n8n-nodes-base.stickyNote - stickyNote
Config choices
Version 1

Block 4 - Webhook Input

Type / Role
n8n-nodes-base.webhook - webhook
Config choices
Version 1.1

Block 5 - Parse Input

Type / Role
n8n-nodes-base.set - set
Config choices
Version 3.4

Block 6 - Download Image

Type / Role
n8n-nodes-base.httpRequest - httpRequest
Config choices
Version 4.2

Block 7 - Extract to Base64

Type / Role
n8n-nodes-base.extractFromFile - extractFromFile
Config choices
Version 1

Block 8 - Prepare for AI

Type / Role
n8n-nodes-base.set - set
Config choices
Version 3.4

Block 9 - Gemini Classify Extract

Type / Role
n8n-nodes-base.httpRequest - httpRequest
Config choices
Version 4.2

Block 10 - Parse AI Results

Type / Role
n8n-nodes-base.set - set
Config choices
Version 3.4

Block 11 - Gemini Structure Data

Type / Role
n8n-nodes-base.httpRequest - httpRequest
Config choices
Version 4.2

Block 12 - Finalize Track

Type / Role
n8n-nodes-base.set - set
Config choices
Version 3.4

Block 13 - API Response

Type / Role
n8n-nodes-base.respondToWebhook - respondToWebhook
Config choices
Version 1.1

Block 14 - Sticky Note5

Type / Role
n8n-nodes-base.stickyNote - stickyNote
Config choices
Version 1

Block 15 - Sticky Note7

Type / Role
n8n-nodes-base.stickyNote - stickyNote
Config choices
Version 1

Block 16 - Sticky Note2

Type / Role
n8n-nodes-base.stickyNote - stickyNote
Config choices
Version 1

Block 17 - Sticky Note4

Type / Role
n8n-nodes-base.stickyNote - stickyNote
Config choices
Version 1

3. Summary Table

Workflow Extract structured data from medical documents with Google Gemini AI
Complexity advanced
Nodes 17
Categories Document Extraction, AI Summarization
Author Louis Chan
Published 12 Jul 2025

4. Reproducing the Workflow from Scratch

  1. 1. Download the workflow JSON

    Use the JSON export at /data/workflows/5917/5917.json as the source template for this automation.

  2. 2. Import the template into n8n

    Open n8n, import the downloaded JSON, and review each node before activating the workflow.

  3. 3. Configure credentials and variables

    Replace placeholder credentials, API keys, webhook URLs, account IDs, and environment-specific values with your own settings.

  4. 4. Test with sample data

    Run the workflow manually or in a staging workspace, inspect node output, and confirm downstream systems receive the expected data.

  5. 5. Activate and monitor

    Enable the workflow only after testing, then monitor executions, errors, and rate limits during the first production runs.

5. General Notes & Resources

Review imported nodes carefully before activation. This catalog entry is intended to help you inspect the workflow structure, understand required services, and find related templates faster.

Node names, credentials, schedules, webhook paths, and external service limits may need adjustment for your workspace.

Frequently asked questions

What does Extract structured data from medical documents with Google Gemini AI do?

How it works Transform medical documents into structured data using Google Gemini AI with enterprise grade accuracy. Classifies document types (receipts, prescriptions, lab reports, clinical notes)...

What do I need before importing this workflow?

Review the workflow JSON, configure any required credentials in n8n, and test the automation in a safe workspace before using it in production.

Can I customize this workflow?

Yes. Use the block-by-block analysis and the downloadable JSON to inspect each node, then adjust credentials, prompts, schedules, filters, or destinations for your Document Extraction, AI Summarization use case.