Course overview
AI tools are already influencing patient care: flagging risks, reading scans, drafting notes, prioritising resources. But while adoption accelerates, the governance, regulatory, and risk frameworks around healthcare AI are still catching up. So, who approves an AI tool for clinical use? Who is liable when it fails? How do you ensure compliance with evolving regulations?
‘AI in Healthcare: Governance, Risk & Strategic Adoption’ is a one-day course designed for professionals in healthcare governance, compliance, legal, regulatory, risk management, and senior leadership roles. No technical background required.
The course builds a practical understanding of AI before diving into what matters most for oversight roles: the regulatory landscape, algorithmic bias and health equity, liability and accountability, institutional governance structures, due diligence, and strategic adoption planning.
The day begins with core AI concepts, demystifying terms like machine learning, natural language processing, and large language models in plain, clinically relevant language. From there, participants explore real-world applications across the care continuum: AI-driven risk stratification and screening in preventive medicine, diagnostic support in radiology and pathology, clinical decision support at the bedside, and intelligent workflow tools that reduce administrative burden.
A dedicated session addresses the critical issues of bias, equity, data privacy, and the ethical responsibilities that come with algorithmic medicine. Participants will engage in exercises evaluating AI tools, interpreting model outputs, and identifying when to trust and, importantly, when to question algorithmic recommendations.
The course closes with a forward-looking discussion on emerging trends, regulatory frameworks, and strategies for integrating AI responsibly within healthcare systems.
CPD Hours: 6
Course Content
- Day 1
- Welcome & foundations of AI
- AI in prevention & early detection
- AI in diagnosis & clinical decision support
- Algorithmic bias, health equity & ethical governance
- Institutional governance & oversight structure
Speakers
Catarina Carrao
Catarina Carrão is the founder of BioSciPons, a life sciences research organisation specialising in health technologies clinical development, evaluation and assessment, with expertise in AI/ML-enabled technologies. She co-ordinates expert teams to bridge the gap between innovation and regulatory compliance, helping developers navigate complex requirements while meeting the expectations of Notified Bodies and the FDA.
Catarina's academic background includes a Marie-Curie Fellowship at Charité Berlin, and Postdoctoral Fellowship at Yale's University Cardiovascular Research Center. She is a Fellow of the American Heart Association (FAHA) since 2013, Delegate of the European Society of Cardiology (ESC), and Professional member of the Health Technology Assessment International (HTAi) organization. She is an expert for the European Commission HaDEA on clinical investigations and Digital Health Technologies, and for the European Innovation and Technology (EIT) Council Health Cluster.
She has presented at RAPS Euroconvergence, the ESC Digital & AI Summit, and DIA Europe on AI/ML medical device regulation, post-market monitoring, and reimbursement pathways. Her recent publications include book chapters and articles on machine learning best practices, AI trustworthiness, and EU MDR/IVDR clinical evaluation.
