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Convert radiology images to patient-friendly reports with GPT-4 Vision & PDF email

Oneclick AI SquadOneclick AI Squad
653 views
2/3/2026
AsynchronousTransformationWebhook ResponseSub-workflowAPI
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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": "john@email.com"
}

⚙️ 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

Want a tailored workflow for your business? Our experts can craft it quickly Contact our team

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

This n8n workflow automates the process of converting radiology image descriptions into easy-to-understand patient reports, leveraging the power of GPT-4 Vision. It then generates a PDF of this report and sends it via email.

What it does

This workflow simplifies the creation and distribution of patient-friendly radiology reports through the following steps:

  1. Triggers Manually: The workflow is designed to be triggered manually, allowing for on-demand processing of radiology image data.
  2. Generates Patient-Friendly Report: It uses a "Code" node to process input data (presumably radiology image descriptions) and format it into a patient-friendly report. The exact transformation logic is defined within the Code node itself.
  3. Waits for Processing: A "Wait" node is included, likely to introduce a delay for any asynchronous processing or to space out API calls if external services are involved in the "Code" node logic.
  4. Generates PDF Report: An "HTTP Request" node is used to interact with an external service (e.g., a PDF generation API) to convert the patient-friendly report into a PDF document.
  5. Sends Email with Report: A "Gmail" node is configured to send the generated PDF report as an attachment via email.
  6. Logs to Google Sheets: Finally, a "Google Sheets" node is used to log details of the processed report, such as the patient information, report summary, or status, into a specified Google Sheet.

Prerequisites/Requirements

To use this workflow, you will need:

  • n8n Instance: A running instance of n8n.
  • Google Sheets Account: Configured credentials for Google Sheets to log report data.
  • Gmail Account: Configured credentials for Gmail to send emails.
  • External PDF Generation Service: An API endpoint for a service that can convert text or HTML into a PDF document, accessible via HTTP.
  • Custom Code (JavaScript): The "Code" node contains custom JavaScript logic. You may need to review and adapt this code to fit your specific data structure and the requirements of GPT-4 Vision or any other AI model used for report generation.

Setup/Usage

  1. Import the Workflow: Import the provided JSON into your n8n instance.
  2. Configure Credentials:
    • Set up your Google Sheets credentials.
    • Set up your Gmail credentials.
  3. Configure HTTP Request Node:
    • Update the "HTTP Request" node with the URL and any necessary authentication for your chosen PDF generation service.
    • Ensure the request body correctly sends the patient-friendly report data to the PDF service.
  4. Review and Customize Code Node:
    • Examine the JavaScript code within the "Code" node. This is where the core logic for transforming radiology descriptions into patient-friendly text resides. You will likely need to integrate with an AI model like GPT-4 Vision here, sending the radiology image data/descriptions and receiving the processed report.
    • Adjust the input and output data structures to match your specific use case.
  5. Configure Gmail Node:
    • Specify the recipient email address(es), subject, and body for the email.
    • Ensure the PDF attachment is correctly mapped from the output of the "HTTP Request" node.
  6. Configure Google Sheets Node:
    • Specify the Google Sheet and tab where you want to log the report data.
    • Map the relevant data fields from the workflow to the columns in your Google Sheet.
  7. Activate the Workflow: Once all configurations are complete, activate the workflow.
  8. Execute Manually: Trigger the workflow manually to process your radiology image data and generate/send the reports.

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