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| # RadioFlow Demo Video Script | |
| ## 3-Minute Competition Video | |
| --- | |
| ## 📋 BEFORE RECORDING - What You Need | |
| ### Images to Use | |
| Use the **sample chest X-rays** in your `sample_data/` folder: | |
| - `real_cxr_1.png` | |
| - `real_cxr_2.jpg` | |
| - `real_cxr_bilateral.jpg` | |
| - `real_cxr_opacity.png` | |
| **⚠️ IMPORTANT**: Only use CHEST X-rays (lungs/heart visible). | |
| Do NOT use shoulder, orthopedic, or other body part X-rays. | |
| ### Checklist | |
| - [ ] Local app running at http://127.0.0.1:7860 | |
| - [ ] Sample X-ray images ready | |
| - [ ] Screen recording software ready (OBS, Loom, QuickTime) | |
| - [ ] Microphone tested | |
| - [ ] Notifications turned off | |
| --- | |
| ## 🎬 THE SCRIPT | |
| ### INTRO (0:00 - 0:20) | |
| **[Screen: Title slide or RadioFlow interface]** | |
| > "Hi, I'm Samarpeet, and this is RadioFlow - a multi-agent AI system for radiology workflows, built for the MedGemma Impact Challenge." | |
| **[Screen: Show the 4-agent diagram or interface]** | |
| > "RadioFlow demonstrates how specialized AI agents can collaborate to assist radiologists - analyzing images, interpreting findings, generating reports, and assessing priority." | |
| --- | |
| ### THE PROBLEM (0:20 - 0:40) | |
| **[Screen: Problem statistics or simple text slide]** | |
| > "Radiologists face a critical challenge: over 700 million imaging studies per year in the US alone, with burnout rates exceeding 30%." | |
| > "The manual workflow of analyzing images, writing reports, and prioritizing cases creates bottlenecks and delays." | |
| > "RadioFlow addresses this with a multi-agent AI approach." | |
| --- | |
| ### ARCHITECTURE (0:40 - 1:10) | |
| **[Screen: Show the RadioFlow interface or architecture diagram]** | |
| > "RadioFlow uses a 4-agent orchestrated pipeline." | |
| **[Point to or highlight each section]** | |
| > "Agent 1, the CXR Analyzer, processes the chest X-ray image." | |
| > "Agent 2, the Finding Interpreter, uses MedGemma to translate findings into clinical language." | |
| > "Agent 3, the Report Generator, creates a structured radiology report using MedGemma." | |
| > "Agent 4, the Priority Router, assesses urgency and determines case routing - also powered by MedGemma." | |
| > "Each agent has a specific job and hands off to the next - this is agentic workflow design." | |
| --- | |
| ### LIVE DEMO (1:10 - 2:10) | |
| **[Screen: RadioFlow Gradio interface - http://127.0.0.1:7860]** | |
| > "Let me show you RadioFlow in action." | |
| **[Upload one of the sample chest X-rays]** | |
| > "I'll upload a chest X-ray. You can also add clinical context like patient history." | |
| **[Type in Clinical History box: "65-year-old with cough and fever"]** | |
| **[Click 'Analyze X-Ray' button]** | |
| > "Now watch as the pipeline processes through each agent..." | |
| **[Wait for processing - about 15-20 seconds with real MedGemma]** | |
| > "Stage 1 analyzes the image... Stage 2 interprets findings with MedGemma... Stage 3 generates the report... Stage 4 assesses priority..." | |
| **[Show the results when ready]** | |
| > "In about 15 seconds, RadioFlow has produced a complete analysis." | |
| **[Click on Report tab]** | |
| > "Here's the structured radiology report - generated by MedGemma with findings, impression, and recommendations." | |
| **[Show Priority section]** | |
| > "The system assessed this as [READ THE PRIORITY LEVEL] priority." | |
| **[Optionally show Visualizations tab]** | |
| > "The visualization shows the agent pipeline and processing metrics." | |
| --- | |
| ### WHY THIS MATTERS (2:10 - 2:40) | |
| **[Screen: Back to main interface or impact slide]** | |
| > "What makes RadioFlow special isn't just the output - it's the architecture." | |
| > "Four specialized agents, each doing one thing well, with clear handoffs between them." | |
| > "This modular design means each agent can be improved independently, debugged clearly, and scaled as needed." | |
| > "MedGemma powers the clinical intelligence - understanding medical terminology and generating professional reports." | |
| > "For production deployment, this architecture could integrate medical imaging AI like CXR Foundation for the image analysis stage." | |
| --- | |
| ### CLOSING (2:40 - 3:00) | |
| **[Screen: Summary or final slide]** | |
| > "RadioFlow: a multi-agent AI system demonstrating how specialized agents can collaborate for radiology workflow automation." | |
| > "Built with Google's MedGemma, targeting both the Main Track and the Agentic Workflow Prize." | |
| > "Thank you for watching!" | |
| **[Screen: Your name and links]** | |
| --- | |
| ## 🎥 Recording Tips | |
| 1. **Speak slowly and clearly** - You have 3 minutes, no need to rush | |
| 2. **Practice once or twice** before recording | |
| 3. **Wait for processing** - The ~15 second MedGemma processing is fine to show | |
| 4. **If something goes wrong** - Just pause and retry that section | |
| 5. **Aim for 2:45-2:55** - Leave buffer under the 3-minute limit | |
| ## 🛠️ Recording Tools | |
| - **Mac**: QuickTime Player (built-in) or OBS Studio (free) | |
| - **Simple option**: Loom (easy screen + audio recording) | |
| - **Editing**: iMovie (Mac) or DaVinci Resolve (free) | |
| ## 📁 Sample Images Location | |
| Your sample X-rays are in: | |
| ``` | |
| /Users/samarpeetgarad/Desktop/competitions/The MedGemma Impact Challenge/sample_data/ | |
| ``` | |
| Use any of these for the demo: | |
| - `real_cxr_1.png` - Good for showing opacity detection | |
| - `real_cxr_2.jpg` - Clear chest X-ray | |
| - `real_cxr_bilateral.jpg` - Shows bilateral findings | |
| - `real_cxr_opacity.png` - Shows opacity findings | |
| --- | |
| ## ✅ Final Checklist | |
| - [ ] Script practiced 2-3 times | |
| - [ ] Local app running and tested | |
| - [ ] Sample image ready to upload | |
| - [ ] Recording software ready | |
| - [ ] Microphone working | |
| - [ ] Notifications off | |
| - [ ] Video under 3 minutes | |
| - [ ] Uploaded to YouTube/Drive and link added to submission | |