START
Kick-off/presentation day CAF: 17/09/2026 (In person in Fano and remotely)
Start: 24/09/2026
Description
Artificial Intelligence is profoundly transforming healthcare systems, affecting clinical, organizational, and decision-making processes. Understanding, evaluating, and managing it is now a key skill for physicians, healthcare professionals, executives, and managers.
Link Campus University’s Advanced Training Course in “Artificial Intelligence Governance in Healthcare” (GIAS) offers a structured programme designed to provide participants with the skills required to guide the implementation of AI in healthcare facilities in an informed, safe, and responsible manner. The programme adopts a systemic rather than a technical-IT approach, integrating Evidence-Based Medicine, the European regulatory framework (AI Act, MDR, EHDS, GDPR), clinical and organizational governance, and risk management.
The course, which lasts 72 hours and is conducted entirely online, consists of 4 theoretical modules, 2 practical workshops, and a final project, fostering dialogue among clinicians, technicians, regulators, and management.
Target Students
The course is aimed at professionals working in the healthcare system who are involved, in various capacities, in technological innovation, evaluation, service organization, and clinical and care governance.
- Physicians and medical specialists;
- Executives and officials of the National and Regional Health Services;
- Directors of simple and complex healthcare facilities;
- Healthcare professionals with a master’s degree;
- Hospital and community pharmacists;
- Biomedical, clinical, and IT engineers working in healthcare;
- Healthcare managers and planning managers;
- Quality, accreditation, and risk management managers;
- Innovation managers and digital transformation leaders;
- Professionals involved in health technology assessment (HTA);
- Data Protection Officers (DPOs) and compliance officers in the healthcare sector.
Purposes
Upon completion of the course the candidates will be able to:
- understand the theoretical and methodological foundations of AI applied to healthcare;
- critically analyze algorithmic models and their methodological limitations;
- integrate the principles of evidence-based medicine (EBM) into the evaluation of AI systems;
- interpret the European (AI Act, MDR, EHDS, GDPR) and national regulatory frameworks;
- assess the safety, efficacy, equity, and sustainability of AI-based solutions;
- design implementation and monitoring models for healthcare facilities;
- govern technological change management processes and manage the associated clinical risk;
- develop organizational frameworks for AI governance.
Didactics
The Higher Education Course lasts 72 hours, divided into:
- Synchronous classes in a virtual classroom to interact directly with instructors according to a scheduled calendar;
- Asynchronous materials (slides, readings, case studies) to explore and reinforce the content;
- Practical workshops (2 workshops) for hands-on exercises and simulations;
- Independent study and research activities to reinforce knowledge;
- Final project to actively apply the content learned.
The program consists of 4 modules (Fundamentals of AI in Healthcare; Evidence-Based Medicine and Methodological Evaluation of AI Systems; European Regulatory Framework and Compliance; Governance, Implementation, and Risk Management).
Tuition Fee
The annual tuition for the registration to the Master is € 1.400.
Registration
Students wishing to enrol may request an appointment with the Orientation Office by calling +39 06 3400 6000.
Furthermore, the candidates may request information directly to the Orientation Office at the following address: segreteriapostgraduate@unilink.it
Admission Requirements
Admission to the course is open to those who meet the minimum requirement of a five-year upper-secondary school diploma (Law 341/1990, Art. 6). It is strongly recommended that applicants hold a bachelor’s degree or equivalent qualification in medicine, health sciences, engineering, computer science, law, economics, or management, in line with the target profiles.
A CAF kick-off event is planned for registered participants and anyone else interested, during which the course and its format will be presented.
Scientific Director
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Prof. Davide Golinelli
Didactic Coordinator
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Prof. Miriana D'Alessandro
Internal Faculty
The Internal Faculty consists of university professors and professionals with many years of proven clinical and scientific experience in the fields of Public Health and Digital Health, Medical Informatics, Evidence-Based Medicine, Health Technology Assessment, European regulation of AI and medical devices, and the governance and management of healthcare organizations. The list of faculty members will be made available before the course begins.
PROGRAMME
The course consists of 4 modules, 2 practical workshops, and a final project, for a total of 72 hours of structured instruction.
Module 1 — Fundamentals of Artificial Intelligence in Healthcare
- Digital Health and AI
- AI models and key tasks in medicine
- Generative AI, LLMs, and operational applications
- Healthcare data, quality, governance, interoperability, and the lifecycle of AI systems
- Transparency, clinical applications, and risks of AI (xAI, clinical/surgical/community applications, automation bias, cognitive sovereignty, and cognitive offload)
Module 2 — Evidence-Based Medicine and Methodological Evaluation of AI Systems
- EBM Applied to AI
- study designs, hierarchy of evidence, and real-world evidence
- internal and external validation and performance metrics
- algorithmic bias and fairness
- clinical, organizational, and economic evaluation, and HTA frameworks for AI systems
Module 3 — European Regulatory Framework and Compliance
- European Regulatory Ecosystem and the AI Act (Principles and Architecture)
- The AI Act as Applied to Healthcare, Italian National Legislation (Law 132/2025), and the EHDS
- GDPR, DPIA, Cybersecurity, and NIS2
- MDR and Software-as-a-Medical-Device (SaMD)
- Professional Liability and Institutional Governance
Module 4 — Governance, Implementation, and Risk Management
- Governance of Innovation and AI in Healthcare Systems
- Change management, stakeholders, and implementation in clinical pathways
- Procurement, organizational policies, and risk management
- Performance monitoring, equity, and sustainability
Applied workshops and final project work
Two applied workshops (Workshop 1 — Critical Analysis of an AI Tool in Healthcare; Workshop 2 — Methodological Evaluation of a Study on AI Systems). The final project, completed individually or in small groups, is followed by a concluding discussion session before the committee.