In February 2025, the TeamUp x Health event was held at Algebra Bernays University, bringing together experts and innovators to discuss the impact of artificial intelligence (AI) on personalized medicine.
As the demand for individualized treatment grows, artificial intelligence (AI) is emerging as a tool to tailor diagnostics, therapies, and patient care to each individual’s unique genetic and clinical profile.
Personalized medicine has the potential to improve treatment effectiveness, reduce side effects, and enhance patient outcomes by leveraging vast amounts of health data to create targeted medical interventions.
Organized by Smion as part of the AI2MED project, this event focused on how AI-driven solutions can enhance precision medicine, making healthcare more efficient, patient-centered, and data-driven.
The panel discussion gathered experts from various fields to share insights on AI’s current and future role in healthcare, highlighting both the opportunities and challenges in integrating AI into personalized treatment strategies. Through an engaging exchange of ideas, the event underscored the need for interdisciplinary collaboration, innovation, and adaptation within medical and regulatory frameworks to fully harness AI’s potential in transforming personalized medicine.
10 Key Takeaways from the Panel Discussion on AI in Personalized Medicine
- AI is already improving diagnostics and treatment
Artificial intelligence enables faster and more precise diagnostic procedures, but medicine, as a conservative field, is slow to adopt new technologies. Prof. Robert Likić, PhD emphasized that AI significantly increases doctors’ efficiency and predicted its growing role in psychotherapy.
- Personalized medicine is still in its early stages
Mario Ravić highlighted that successful implementation of personalized medicine requires high-quality research and collaboration with institutions. He also pointed out legal challenges, such as GDPR regulations, and the lack of structured data in Croatia.
- Legal framework and regulations slow down progress
GDPR and other legal challenges pose obstacles to the development of AI solutions in healthcare. Experts emphasized the need for a better legislative framework to facilitate the use of health data for research and innovation.
- The Croatian healthcare system is not ready for complete AI transformation
Ivica Belina warned that there is no unified hospital system and that the management of health data is poorly regulated. Despite this, initiatives such as the Croatian Health Data Center (CHDC) and the research network for tumors show positive progress toward digitization.
- Collaborations and research projects are key to progress
Despite challenges, collaborations between institutions, startups, and research centers show potential for advancing personalized medicine through AI. Experts agreed that education and regulatory adaptation are necessary for faster adoption of innovations in healthcare.
- Lack of structured data hinders progress
One of the key challenges of personalized medicine in Croatia is the lack of high-quality and organized medical data. Without adequate databases, the development and application of AI in healthcare remain limited, slowing down innovation and diagnostic efficiency.
- AI can support psychotherapy and improve mental healthcare access
AI tools like ChatGPT have the potential to assist in psychotherapy, particularly in areas with limited access to mental health professionals, such as remote islands. While not a complete replacement for human therapists, AI could serve as a support system for initial consultations and basic guidance.
- Patients’ reluctance to share medical data impacts research
Many patients avoid recording certain conditions in public healthcare systems due to concerns about privacy, preferring private healthcare instead. This fragmentation of medical records makes it difficult for AI models to analyze comprehensive patient histories, further slowing down progress in personalized medicine.
- Education is crucial for AI adoption in healthcare
Since medicine is traditionally a conservative field, healthcare professionals often hesitate to adopt new technologies. Experts emphasized the importance of AI education and training for doctors, researchers, and policymakers to ensure a smoother integration of AI in personalized medicine. Understanding AI tools and data-driven decision-making will be essential for future medical professionals.
- Raising public awareness and AI literacy is necessary
The discussion on AI’s role in psychotherapy and mental healthcare highlighted the need for broader public education on AI-driven medical solutions. Misinformation and skepticism can slow down adoption, so awareness campaigns and AI literacy initiatives are essential to help patients and healthcare providers trust and effectively use AI-based treatments.
Conclusion
The panel discussion demonstrated that AI offers tremendous opportunities for improving personalized medicine, but significant obstacles remain in its widespread adoption. Legal regulations, slow system adaptation, and the lack of structured data hinder progress, but positive steps through collaborations and research provide optimism for the future. The key to success lies in education, strengthening infrastructure, and adapting the legal framework to enable safer and more efficient AI implementation in healthcare.
