Spencer S. Eccles Health Sciences Library, University of Utah
Abstract
Homonymous visual field (VF) defects are usually an indicator of serious intracranial pathology but may often be subtle and difficult to detect. The utility of artificial intelligence (AI) applications in ophthalmology are becoming increasingly recognized. We aimed to develop an automated deep learning AI model to accurately identify homonymous VF defects from automated perimetry
