Kyung-Min Roh
Papers
3
Total Citations
22
H-Index
3
About
Kyung-Min Roh is a pioneering researcher at the intersection of robotics, ophthalmology, and artificial intelligence, whose work is revolutionizing point-of-care retinal imaging. His primary research areas include autonomous robotic systems for medical imaging, deep learning in ophthalmology, and emergency department diagnostics. Roh’s major contribution is the development of a robotically aligned optical coherence tomography (RAOCT) system that enables contactless, autonomous retinal imaging—a critical advancement for non-specialist settings. His pilot study on RAOCT in emergency department patients (12 citations) demonstrated that emergency physicians could achieve diagnostic performance comparable to ophthalmologists, while his RobOCTNet deep learning model (6 citations) further automated the detection of referable posterior segment pathology. Roh’s work has been published in leading journals and represents a paradigm shift in teleophthalmology, potentially reducing vision loss from delayed diagnoses. With a growing citation impact, his research is foundational for integrating autonomous imaging into acute care, making advanced retinal screening accessible outside traditional clinics. Roh’s innovations promise to transform emergency medicine and global eye health.
Research Focus
Key Achievements
Top Papers
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