Our Work

In this scoping review, we evaluated the performance of artificial intelligence (AI) in clinical radiology practice and examined health professionals' perspectives regarding AI use in radiology.

Diabetic retinopathy can be prevented with screening and early detection. We hypothesized that autonomous artificial intelligence (AI) diabetic eye exams at the point-of-care would increase diabetic eye exam completion rates in a racially and ethnically diverse youth population

Guest Speaker: Chien-Ming Huang, John C. Malone Assistant Professor, Johns Hopkins Department of Computer Science; Director, Johns Hopkins Intuitive Computing Laboratory; and Member, Johns Hopkins Laboratory for Computational Sensing and Robotics.