VIDEO_SCRIPT.md

# 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