Introduction & Presentation
Orientation to TEF-Health and to the disruptive blended-learning pedagogy used across the curriculum, including TRL/CML maturity concepts and an overview of AI & deep learning in health.
- Introduction
- Pedagogy
Learning track
Blended-Learning Curriculum
A blended-learning curriculum for Health-AI innovators — from pedagogy and ethics to clinical evaluation and entrepreneurship.
- 8 courses
- 82 lessons
World of Health
How national healthcare systems work across Europe, and how clinical data warehouses and population data feed AI-driven healthcare.
- General
- Clinical Data Warehouse
- Healthcare systems
Regulation
Regulatory landscape for medical AI — homologation, certification and the EU AI Act, from a Notified Body perspective.
- Notified Body
Ethics
Biomedical ethics for AI in health: from foundational principles and co-design methods to concrete use cases — bias, trustworthy AI, robotics in care, cyber security.
- Introduction
- Methods
- Use cases
Health Data — CDW & Data Lake
How health data is collected, structured, labelled and contextualised, and how Clinical Data Warehouses fit into the AI software lifecycle (MDR / IVDR).
- Data collection, structuring & labelling
- Clinical Data Warehouse
- Contextualization
- Software AI
Clinical Evaluation
From clinical research design and stakeholder duties to validating AI software in the clinic — usability, federated learning, real-world evaluation case studies.
- Clinical Assessment
- Software AI
Health AI Entrepreneurship
The full Health-AI entrepreneur journey: value proposition, customers, technology, funding, strategy and scale-up.
- Entrepreneurial spirit
Keynote
Pitching, storytelling and non-verbal communication for Health-AI founders, plus offer-and-demand perspectives on medical devices and surgical robotics.
- Communication
- Offer and Demand