📚 Syllabus & Course Curriculum
Data Science & Analytics
Module-by-module breakdown of Innovations in AI for Diagnostic & Medical Devices, from foundations to a certified capstone project.
Device Context
• Software as a Medical Device: definitions, classification and intended use statements
• The intended-use boundary and how a claim changes the regulatory burden
• Combination products and AI embedded in hardware
Design Controls
• ISO 13485 design controls applied to a machine-learning workflow
• Requirements, traceability and design history for a learning system
• ISO 14971 risk management and hazard analysis for AI failure modes
Evidence
• Analytical validation versus clinical validation versus clinical utility
• Study design for a diagnostic claim, including reference standard selection
• Statistical planning: sample size, subgroup analysis and pre-specification
Change
• Locked versus adaptive algorithms and predetermined change control plans
• Version control, retraining triggers and documenting what changed
• Real-world performance monitoring and post-market surveillance duties
Market
• Regulatory pathways across FDA, EU MDR and CDSCO, and their divergence
• Cybersecurity requirements for connected diagnostic devices
• Reimbursement and the health-economic case a purchaser will demand
Earn government-registered certification in Innovations in AI for Diagnostic & Medical Devices
e-Certificate and e-Marksheet issued on successful completion.
