On Thursday, November 20, Aleksandra Dragičević, Advisor for Artificial Intelligence in Healthcare at the Center for the Fourth Industrial Revolution Serbia, participated in the Data Science Conference 2025, one of the largest regional conferences dedicated to advanced data analytics and artificial intelligence. Dragičević took part in a breakout session titled “AI Boosted Research,” alongside Anđelka Kovačević, Dragana Ilić, and Marija Mitrović Dankulov. Following the individual presentations, a panel discussion was held.
Dragičević delivered a presentation titled “AI-Boosted Research in Healthcare: From Data to Clinical Implementation in Serbia,” in which she discussed current national initiatives aimed at ensuring the safe and responsible use of AI within Serbia’s healthcare system.
In her presentation, she emphasized the key role of the Office for IT and eGovernment and the Center for the Fourth Industrial Revolution Serbia in advancing digital health and building the foundations of an AI-ready healthcare ecosystem. She highlighted national data platforms, cross-sector partnerships, and strategic initiatives such as the National AI-Health Testbed and the AI Implementation Framework for Healthcare.
According to Dragičević, these projects enable faster and more reliable adoption of innovative AI solutions in clinical settings, strengthen the regulatory preparedness of the healthcare system, and support evidence-based decision-making.
“C4IR Serbia is committed to developing the infrastructure, policies, and tools that enable the safe, transparent, and responsible introduction of AI technologies into the healthcare system. Our goal is to provide healthcare institutions in Serbia with an environment where they can test, validate, and implement innovative solutions in full alignment with international standards,” Dragičević emphasized. The session “AI Boosted Research” gathered experts who actively contribute to the development of Serbia’s AI ecosystem, and the discussion that followed addressed key questions related to setting priorities, building data infrastructure, and bridging the gap between research and real-world clinical implementation.
