AI in Diagnostic & Medical Devices

Module 1: AI in Diagnostics and Medical Devices

• Introduction to AI in Diagnostics
• Workflow of AI-Enabled Devices
• Adoption Drivers and Common Pitfalls

Module 2: Data and Signal Fundamentals

• Types of Data in Diagnostic Systems
• Data Quality and Preprocessing
• Ground Truth and Reference Standards

Module 3: Model Approaches for Diagnostic Tasks

• Detection and Classification
• Segmentation and Measurement Support
• Anomaly Detection and Fault Monitoring

Module 4: Evaluation and Performance Reporting

• Core Performance Metrics
• Calibration and Thresholds
• Contextual Performance Reporting

Module 5: Clinical Validation and Deployment Readiness

• Validation Strategy
• Workflow Integration
• Building Trust in Deployment

Module 6: Safety, Reliability, and Risk Management

• Failure Modes and Safe Design
• Alarm Management and Reliability
• Incident and Corrective Action Planning

Module 7: Post-Deployment Monitoring

• Drift and Data Shift
• Ongoing Performance Oversight
• Controlled Updates and Change Management