AI & Machine Learning
Understanding the AI technology
Overview
SRAT-AI uses advanced machine learning for risk prediction. Natural language processing generates clinical rationales. Computer vision analyzes imaging and gait videos. Explainability features show which factors influenced each prediction, ensuring transparency and clinical trust.
Key Features
Advanced machine learning models
Natural language processing integration
Explainability visualizations
Continuous model improvement
Evidence-based validation
How to Use This Feature
1
Access the Feature
Navigate to this feature from the main dashboard
2
Enter Required Information
Provide all necessary patient or clinical data
3
Run Analysis
Execute the feature to generate results
4
Review Output
Carefully review the generated information
5
Take Action
Use the insights to inform your clinical decisions
Best Practices
- Ensure data accuracy and completeness
- Review AI outputs critically with clinical judgment
- Document your decision-making process
- Use the feature regularly to maximize value
- Contact support if you encounter issues
Pro Tips
- 💡Explore all features to discover hidden capabilities
- 💡Use the search function in Help Center for quick answers
- 💡Check release notes for new features and improvements
Related Resources
Video Tutorial
Watch a comprehensive walkthrough of this feature
Video tutorial coming soon
Contact support to request a personalized demo