Artificial Intelligence for Healthcare Professionals - Part 2: Advanced Applications and Responsible Integration
As Artificial Intelligence becomes more deeply integrated into healthcare systems, its role extends beyond diagnostics and decision support into more complex domains such as immersive therapeutic environments, biosensing technologies, telemedicine infrastructures, and human–AI collaborative systems.
This training explores the next layer of AI in healthcare, focusing on how advanced technologies are reshaping clinical practice and enabling new forms of care delivery. Participants are introduced to immersive systems such as Virtual Reality and Augmented Reality used in rehabilitation and therapy, as well as biosensing technologies that capture physiological and behavioral signals to support clinical assessment.
The course also examines telemedicine and remote healthcare systems, including AI-supported remote diagnostics and tele-operated medical procedures. These developments are contextualized within a broader framework of human-centered AI, where clinicians remain central in interpreting, supervising, and guiding AI-supported systems. Real-world case studies demonstrate applications in mental healthcare, including emotion-aware systems and AI-supported therapeutic interventions such as art-based therapy approaches. These examples illustrate how AI can support clinicians in delivering more personalized and context-aware care while maintaining professional oversight.
Finally, the course addresses ethical, regulatory, and safety considerations, including GDPR, the EU AI Act, and clinical accountability in AI-supported healthcare systems.
Content
This module is structured over two days:
Day 1: Emerging Technologies in Healthcare
Immersive Technologies in Healthcare
- Virtual Reality (VR), Augmented Reality (AR), and Extended Reality (XR)
- Applications in surgical training, rehabilitation, and therapy
- Interactive medical environments and simulation
Biosensing and Neurotechnology
- Brain–computer interfaces (BCI) with EEG & fNIRS
- Eye tracking and physiological monitoring
- AI in Affective computing with physiological sensing
- Objective measurement of cognitive and behavioral responses with AI
Telemedicine and Remote Healthcare
- AI in telemedicine platforms and digital health ecosystems
- AI-supported remote diagnostics
- tele-robotic systems and remote surgical technologies case study and remote interaction demo & workshop
Human-Centered Artificial Intelligence (HCAI)
- Human agency, transparency, ethics, and accountability
- Human-centered recommender systems
- Case studies in art, culture, and multi-stakeholder personalization
Day 2: Responsible AI and the Future of Healthcare
Human-Centered Artificial Intelligence
- clinician–AI collaboration
- explainability and transparency
- avoiding automation bias
Ethical and Regulatory Frameworks
- GDPR, HIPPA and healthcare data protection
- EU AI Act and medical device regulations
- accountability and responsible system design
Case Studies in AI for Healthcare
Examples include:
- AI-assisted diagnostics (AI in Radiology)
- digital therapeutics and rehabilitation systems
- Tele-operation
- AI-supported mental healthcare
- creative therapeutic approaches such as art-based interventions
Future Directions in AI for Healthcare
- AI-augmented clinical environments (Immersive show case XR)
- intelligent hospitals and healthcare ecosystems
- emerging trends in digital medicine and healthcare innovation
Learning Outcomes
By the end of the course, participants will be able to:
- Understand advanced AI applications in healthcare
- Evaluate emerging technologies such as immersive systems and biosensing
- Understand human-centered AI and clinician–AI collaboration
- Assess risks and limitations of advanced AI systems
- Navigate ethical and regulatory requirements
- Critically reflect on future AI-enabled healthcare systems
Training Method
Two-day intensive training combining:
- lectures and advanced concepts
- demonstrations of technologies
- case studies and applied discussions
- interactive sessions
Certification
Certificate of ParticipationPrerequisites
- Professional background in healthcare
- Prior exposure to AI concepts, or completion of Artificial Intelligence for Healthcare Professionals – Part 1 (or equivalent knowledge)
- No technical or programming background required
Planning and location
09:30 - 17:00
09:30 - 17:00