Artificial intelligence (AI) is creating new opportunities in healthcare, from helping doctors detect disease earlier to anticipating complications and tailoring treatments to individual patients. Yet turning clinical data into tools that can support real-world medical decisions remains a significant challenge.

On June 16, researchers from UNIST and Asan Medical Center came together to discuss how advances in AI, data science, and clinical medicine can help bridge that gap. 

A recurring question throughout the discussions was how AI can help clinicians make better decisions in complex healthcare settings. Researchers shared work on digital pathology, critical care analytics, predictive modeling, and other approaches aimed at turning clinical data into actionable insights for patient care.

More than 40 researchers and clinicians from UNIST and Asan Medical Center participated in the discussions, bringing together expertise in AI, biomedical engineering, computer science, and clinical medicine. Topics ranged from disease diagnosis and prognosis to patient monitoring and treatment planning.

Several presentations highlighted areas where AI is beginning to show promise in clinical practice, including the analysis of data generated in operating rooms and intensive care units, digital pathology for disease detection, and predictive models designed to anticipate patient outcomes. Researchers also discussed digital twin approaches that could help simulate disease progression and support more personalized treatment strategies.

A recurring theme throughout the event was the importance of defining meaningful clinical problems before developing technical solutions. Participants emphasized that successful medical AI depends not only on stronger algorithms, but also on close engagement with clinicians who understand the realities of patient care.

The discussions also highlighted how the two institutions bring different capabilities to the partnership. UNIST continues to expand its capabilities in large-scale medical data analysis through advanced AI research and high-performance computing resources. Asan Medical Center, meanwhile, is developing an Integrated Data Platform (IDP) to support the secure and efficient use of clinical data for research.

Since launching their partnership earlier this year, the two institutions have been exploring new opportunities for researcher exchange and joint projects that combine clinical expertise with advances in artificial intelligence. Areas of interest include digital pathology, critical care analytics, and predictive models that can help doctors make more informed decisions and deliver more personalized care.

“This gathering provided an opportunity to connect UNIST's strengths in artificial intelligence and data science with Asan Medical Center's clinical expertise,” said Dean Seungjae Baek of UNIST Graduate School of Health Science and Technology. “By bringing researchers together around real challenges in healthcare, we hope to develop research that can ultimately improve patient outcomes.”

Dong Hyun Yang, Director of the AI Innovation Support Office at Asan Medical Center, said, “Combining extensive clinical data with advanced AI technologies creates new opportunities to address complex challenges in healthcare. We look forward to expanding research that supports more accurate predictions, better clinical decision-making, and increasingly personalized patient care.”