To identify and characterize concept coverage gaps of ophthalmology examination data elements within the Cerner Millennium electronic health record (EHR) implementations by the Observational Health Data Sciences and Informatics (OHDSI) Observational Medical Outcomes Partnership (OMOP) common data model (CDM)

Retinopathy of prematurity (ROP) stage is defined by the visual appearance of the vascular-avascular border, which reflects a spectrum of pathologic neurovascular tissue (NVT). Previous work demonstrated that the thickness of the ridge lesion, measured using optical coherence tomography (OCT), corresponds to higher clinical diagnosis of stage. This study evaluates whether the volume of anomalous NVT (ANVTV), defined as abnormal tissue protruding from the regular contour of the retina, can be measured automatically using deep learning to develop quantitative OCT-based biomarkers in ROP.

To validate the performance of the Notal OCT Analyzer (NOA) in processing self-administered OCT images from an OCT system designed for home use (home OCT [HOCT]) as part of a pivotal study aimed at achieving de novo United States Food and Drug Admininstration marketing authorization.

To quantitatively assess the retinal vascular tortuosity of patients with sickle cell disease (SCD) and retinopathy (SCR) using an automated deep learning (DL)-based pipeline.