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Convert Radiology Images to Patient-Friendly Reports with GPT-4 Vision & PDF Email

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Last update 3 days ago

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This automated n8n workflow transforms uploaded radiology images into professional, patient-friendly PDF reports. It uses AI-powered image analysis to interpret medical scans, simplify technical terms, and produce clear explanations. The reports are formatted, converted to PDF, stored in a database, and sent directly to patients via email, ensuring both accuracy and accessibility.

🏥 Workflow Overview:

Simple Process Flow:

  1. Upload Image → 2. AI Analysis → 3. Generate Report → 4. Send to Patient

🔧 How It Works:

  1. Webhook Trigger - Receives image uploads via POST request
  2. Extract Image Data - Processes patient info and image data
  3. AI Image Analysis - Uses GPT-4 Vision to analyze the radiology image
  4. Process Analysis - Structures the AI response into readable sections
  5. Generate PDF Report - Creates a beautiful HTML report
  6. Convert to PDF - Converts HTML to downloadable PDF
  7. Save to Database - Logs all reports in Google Sheets
  8. Email Patient - Sends the report via email
  9. Return Response - Confirms successful processing

📊 Key Features:

  • AI-Powered Analysis using GPT-4 Vision
  • Patient-Friendly Language (no medical jargon)
  • Professional PDF Reports with clear sections
  • Email Delivery with report attachment
  • Database Logging for record keeping
  • Simple Webhook Interface for easy integration

🚀 Usage Example:

Send POST request to webhook with:

{
  "patient_name": "John Smith",
  "patient_id": "P12345",
  "scan_type": "X-Ray",
  "body_part": "Chest",
  "image_url": "https://example.com/xray.jpg",
  "doctor_name": "Dr. Johnson",
  "patient_email": "[email protected]"
}

⚙️ Required Setup:

  1. OpenAI API - For GPT-4 Vision image analysis
  2. PDF Conversion Service - HTML to PDF converter
  3. Gmail Account - For sending reports
  4. Google Sheets - For logging reports
  5. Replace YOUR_REPORTS_SHEET_ID with your actual sheet ID

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