A Catalog of Public Glaucoma Datasets for Machine Learning Applications
Riley Kiefer, Muhammad Rizwan Abid, Jessica Steen, Mahsa Raeisi Ardali, Ehsan Amjadian
Abstract
Glaucoma is a leading eye disease impacting millions of people. While the number of public glaucoma datasets are limited, those available are diverse in the population of patients, glaucoma subtypes, and other features. The complexity of disease datasets like glaucoma requires detailed catalogs to accurately describe the numerous dataset features. To increase the accessibility of glaucoma research, this work provides a comprehensive glaucoma dataset catalog by standardizing various dataset attributes into several organized tables. Data documentation can ensure high-quality AI models.
Topics & Concepts
GlaucomaComputer scienceDocumentationPopulationData miningArtificial intelligenceData scienceMedicineOphthalmologyEnvironmental healthProgramming languageRetinal Imaging and AnalysisGlaucoma and retinal disordersDigital Imaging for Blood Diseases