radioflow / VIDEO_SCRIPT.md
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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