Research Areas
AI-driven Radiology Applications
This area leverages AI to perform in-depth analyses of radiological images covering the entire human body, including modalities such as X-ray, CT, MRI, and Ultrasound. Our objective is to demonstrate the clinical utility of AI in radiology applications and ultimately enable radiologists to integrate these solutions effectively into real-world clinical settings.
Multi-modal Biomedical Data Analysis
This area comprehensively analyzes diverse multi-modal biomedical data—including endoscopic images, bio-signals, omics data, and EHR—to offer in-depth insights into disease mechanisms and facilitate personalized medicine. Our objective is to leverage hospital real-world data (RWD) to expand the applications of a Large Multi-modal Model (LMM) and Agentic AI, and to validate them in clinical settings.
Advanced AI Techniques for Medical Applications
This area is dedicated to exploring innovative AI methods specifically designed for medical applications. We focus on developing novel algorithms and optimization strategies to address a wide range of challenges in the clinical domain. Our objective goes beyond methodological advancement; we aim to create AI solutions that seamlessly integrate with clinical workflows and settings, ultimately enhancing patient care.