AI in Diagnostic & Medical Devices

Aim

Program Objectives

Program Structure

• 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

  Module 8: Governance and Compliance Readiness

  • Documentation for AI-Enabled Devices
  • Privacy and Security Basics
  • Change Control and Lifecycle Governance

Who Should Enrol?

Program Outcomes

Fee Structure

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What You’ll Gain