Convert radiology images to patient-friendly reports with GPT-4 Vision & PDF email
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: Upload Image → 2. AI Analysis → 3. Generate Report → 4. Send to Patient 🔧 How It Works: Webhook Trigger - Receives image uploads via POST request Extract Image Data - Processes patient info and image data AI Image Analysis - Uses GPT-4 Vision to analyze the radiology image Process Analysis - Structures the AI response into readable sections Generate PDF Report - Creates a beautiful HTML report Convert to PDF - Converts HTML to downloadable PDF Save to Database - Logs all reports in Google Sheets Email Patient - Sends the report via email 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: json { "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: OpenAI API - For GPT-4 Vision image analysis PDF Conversion Service - HTML to PDF converter Gmail Account - For sending reports Google Sheets - For logging reports Replace YOURREPORTSSHEET_ID with your actual sheet ID Want a tailored workflow for your business? Our experts can craft it quickly Contact our team
By Oneclick AI SquadAWS EC2 lifecycle manager with AI chat agent (describe, start, stop, reboot)
EC2 Lifecycle Manager with AI Chat Agent (Describe, Start, Stop, Reboot, Terminate) Watch the demo video below: [](https://youtu.be/C1s0AM1_ho0) Who’s it for This workflow is designed for DevOps engineers and cloud administrators who want to manage AWS EC2 instances directly from chat platforms (Slack, Teams, Telegram, etc.) using natural language. It helps engineers quickly check EC2 instance status, start/stop servers, reboot instances, or terminate unused machines — without logging into the AWS console. How it works / What it does A chat message (command) from the engineer triggers the workflow. The EC2 Manager AI Agent interprets the request using the AI chat model and memory. The agent decides which AWS EC2 action to perform: DescribeInstances → List or check status of EC2 instances. StartInstances → Boot up stopped instances. StopInstances → Gracefully shut down running instances. RebootInstances → Restart instances without stopping them. TerminateInstances → Permanently delete instances. The selected tool (API call) is executed via an HTTP Request to the AWS EC2 endpoint. The agent replies back in chat with the result (confirmation, instance status, errors, etc.). How to set up Add Chat Trigger Connect your chatbot platform (Slack/Telegram/Teams) to n8n. Configure the “When chat message received” node. Configure OpenAI Chat Model Select a supported LLM (GPT-4, GPT-4.1, GPT-5, etc.). Add system and user prompts to define behavior (EC2 assistant role). Add Memory Use Simple Memory to keep track of context (e.g., instance IDs, region, last action). Connect EC2 API Tools Create HTTP Request nodes for: Describe Instances Start Instance Stop Instance Reboot Instance Terminate Instance Use AWS credentials with Signature V4 authentication. API endpoint: https://ec2.{region}.amazonaws.com/ Link Tools to Agent Attach all EC2 tools to the EC2 Manager AI Agent node. Ensure the agent can choose which tool to call based on user input. Requirements n8n instance (self-hosted or cloud). Chat platform integration (Slack, Teams, or Telegram). OpenAI (or other LLM) credentials. AWS IAM user with EC2 permissions: ec2:DescribeInstances ec2:StartInstances ec2:StopInstances ec2:RebootInstances ec2:TerminateInstances AWS region configured for API calls. How to customize the workflow Add safety checks: Require explicit confirmation before running Stop or Terminate. Region flexibility: Add support for multi-region management by letting the user specify the region in chat. Tag-based filters: Extend DescribeInstances to return only instances matching specific tags (e.g., env=dev). Cost-saving automation: Add scheduled rules to automatically stop instances outside working hours. Enhanced chatbot UX: Format responses into tables or rich messages in Slack/Teams. Audit logging: Store each action (who/what/when) into a database or Google Sheets for compliance.
By Trung TranAutomated Twitter following with hashtag targeting, Phantombuster, and GPT-4o
Who’s it for Growth marketers, community managers, and personal-brand builders who want to steadily grow their Twitter (X) network by following new, relevant accounts on autopilot—while respecting daily limits. How it works / What it does Schedule Trigger fires every hour at a specified minute. Select Cookie picks a rotating Twitter session-cookie based on time slices. AI Agent creates a realistic AI/BPA hashtag. Phantombuster Hashtag Agent scrapes recent tweets → extracts profile handles. Set Item builds a small CSV with one profile; Launch AF Agent instructs the Phantombuster Auto-follow agent to follow it. Rate-limit nodes cap follows to roughly 50-80 per day. How to set up Add credentials: Phantombuster API, SharePoint OAuth2, OpenAI API key. In SharePoint › “Phantombuster” folder create: • twittersessioncookies.txt – one cookie per line. Adjust schedule or search parameters as needed. Activate the workflow; it will run hourly and follow 1 new profile each launch. Requirements n8n 1.33 + Phantombuster Growth plan (API access) OpenAI account Microsoft 365 SharePoint tenant How to customize Change niche: edit hashtag prompt in AI Agent. Follow more accounts: raise numberOfAddsPerLaunch and schedule frequency. Use Google Drive/Dropbox instead of SharePoint: swap the cookie download node.
By plemeoAutomated trip weather forecasts from Google Calendar to Telegram
How it works This workflow for trip weather forecasting is event-driven, starting when a calendar event is created or updated, and provides timely weather alerts and forecasts tailored to your travel dates and locations. Overall, this workflow efficiently integrates calendar travel plans with real-time and updated weather intelligence for ultimate travel preparedness and peace of mind. From the creator If you’re jetting off frequently, bouncing between time zones, juggling meetings, and squeezing every drop of life out of travel, you need this flow. This ain’t your grandma’s weather app. It’s a bulletproof system that scans your calendar, mines your trips, and delivers laser-targeted weather intel and urgent alerts, right when you need it. No more surprises. No more scrambling. Just real-time weather mastery that saves your schedule. You’re not just traveling: you’re dominating. This flow makes sure the only thing you worry about is your next move, not whether the weather’s gonna ruin it. Time to upgrade from a tourist to a boss. Step-by-step 📅 Google Calendar Triggers (Event Created/Updated): The workflow starts immediately upon creation or update of any calendar event, enabling real-time detection of new or changed travel plans. ✈ Identify Trips: Filters these calendar events to detect travel-related trips by matching keywords such as "trip," "flight," or "vacation" in titles or descriptions. 📍Extract Locations: Parses each trip event’s details to extract start and end dates and the trip destination from the summary/description/location fields. 🌐 Build interrogation URL: Constructs a Visual Crossing API request URL dynamically based on the extracted trip location and dates, including daily forecasts and alerts. Fetches the detailed weather forecast and alert data for the trip location and duration right after detecting the event. Formats the raw weather data into a readable summary 🌤️🌪🌀 including temperatures, precipitation probabilities, conditions, and eventual severe weather alerts. 📲 📧 Send Forecast: Sends the forecast summary with alerts via Telegram to keep the user informed instantly. ⌛One day before the trip: Pauses the workflow until exactly one day before the trip start date, ensuring a timely second fetch when more accurate or updated weather data is available and the updated forecast is sent. Optional You can replace the Telegram node with email, WhatsApp, Slack, SMS notifications, or add multiple notification nodes to receive them across all desired channels.
By Razvan Bara