Ailin Song, Jay B Lusk, Kyung-Min Roh, S Tammy Hsu, Nita G Valikodath, Eleonora M Lad, Kelly W Muir, Matthew M Engelhard, Alexander T Limkakeng, Joseph A Izatt, Ryan P McNabb, Anthony N Kuo
PURPOSE: To evaluate the diagnostic performance of a robotically aligned optical coherence tomography (RAOCT) system coupled with a deep learning model in detecting referable posterior segment pathology in OCT images of emergency department patients. METHODS: A deep learning model, RobOCTNet, was trained and internally tested to classify OCT images as referable versus non-referable for ophthalmology consultation. For external testing, emergency department patients with signs or symptoms warranting evaluation of the posterior segment were imaged with RAOCT...
March 1, 2024: Translational Vision Science & Technology