README.md

metadata

title: Real Perfusion Monitoring System - Full Simulation
emoji: 🏥
colorFrom: blue
colorTo: purple
sdk: gradio
sdk_version: 4.44.0
app_file: app.py
pinned: false
license: mit

🏥 Real Perfusion Monitoring System - Full Simulation

Complete DQN-powered perfusion monitoring with trained models and real simulation physics.

🚀 Features

• Real DQN Agents: Uses actual trained Deep Q-Network models
• Full Simulation Physics: Complete perfusion system modeling
• Real-Time Monitoring: Live parameter tracking with safety zones
• Professional Interface: Medical-grade dashboard design
• Dual Scenarios: Eye perfusion and VCA perfusion support

🧠 What Makes This Special

Real AI Models

• Trained on thousands of simulation episodes
• Learned optimal perfusion control strategies
• Validated performance on 24-hour scenarios

Complete Physics

• Multi-organ system interactions
• Realistic parameter evolution
• Critical event detection
• Professional medical parameter ranges

Smart Safety System

• 🟢 Safe Zone: Optimal parameter ranges
• 🟡 Warning Zone: Requires attention
• 🔴 Critical Zone: Immediate intervention needed

📊 Parameters Monitored

1. Temperature (35-40°C): Core/perfusate temperature control
2. VR (Vascular Resistance): Blood vessel resistance management
3. pH (7.0-7.8): Acid-base balance maintenance
4. pvO2 (50-700): Partial pressure of oxygen
5. Glucose (3-20 mM): Blood sugar regulation
6. Insulin (5-80 mU): Hormone control

🎯 How to Use

1. Select Scenario: Choose Eye or VCA perfusion
2. Start Evaluation: Watch real AI make decisions
3. Monitor Progress: Follow 24-hour simulation
4. Observe AI Strategy: See intelligent parameter control

🏆 Applications

• Medical Device Control: Automated perfusion systems
• AI Research: Reinforcement learning in healthcare
• Clinical Training: Understanding AI-assisted procedures
• Safety Validation: Testing AI decision-making

---

Powered by PyTorch, Gradio, and advanced deep reinforcement learning.