We are pleased to announce that our team has published a new review paper in the Journal of the Korean Society of Radiology (JKSR), Special Issue: Informatics and AI. This review examines continual learning as a practical framework for maintaining artificial intelligence models in medical imaging. AI models for medical imaging are typically trained once and deployed unchanged, yet scanners, protocols, and patient populations continue to evolve, and performance degrades accord

We are pleased to announce that our team has published a new paper in Information Fusion (Impact Factor: 17.4), one of the leading journals in the field of information fusion and multimodal learning. This study addresses clinical prediction as an incomplete information fusion problem, where the set of observable modalities—coded patient context, lab or vital trajectories, and free-text documentation—varies across care workflows and observation timepoints. The proposed framewo

Prof. Yu Rang Park has been selected as a 2026 Heo Won Professor , an award recognizing outstanding research excellence and contributions to the advancement of medical science. This recognition highlights her continued contributions to advancing data-driven approaches in medicine.