This n8n workflow automates the extraction and classification of medical documents using Google Gemini AI, streamlining medical data processing for healthcare providers and insurers. It begins with an external webhook that receives requests with an image URL and optional metadata such as document type or language. The workflow then downloads the image and converts it into base64 format, preparing it for AI analysis.
The core of the workflow involves sending the image data to Google Gemini’s API for classification and OCR text extraction. The AI model classifies the document into categories like medical reports or prescriptions, extracting all visible text with high accuracy and supporting multiple languages. The results are parsed and structured according to a comprehensive medical document taxonomy, including details like patient info, provider details, financial data, and medical specifics.
Finally, the workflow compiles detailed quality metrics, token usage for cost tracking, and processing metadata. It responds to the initial webhook with a structured JSON object containing the analysis results, which can be integrated into medical records, billing systems, or insurance claims. This automation reduces manual effort, ensures consistency, and accelerates document processing workflows in healthcare environments.
This setup is ideal for healthcare organizations aiming to automate the review and extraction of structured data from medical documents efficiently and accurately.
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