Barriers to Extracting and Harmonizing Glaucoma Testing Data: Gaps, Shortcomings, and the Pursuit of FAIRness
Year: 2024
Type: article
Abstract: We describe potential improvements and barriers to data FAIRness in glaucoma testing and imaging, aiming to inform future efforts to standardize and enhance data availability for research.
Source: Ophthalmology Science
Authors: Niloofar Radgoudarzi, Shahin Hallaj, Michael V. Boland, Brian Stagg, Sophia Y. Wang, Benjamin Xu, Swarup S. Swaminathan, Eric N. Brown, Aiyin Chen, Catherine Q. Sun, Dilru C. Amarasekera, Jonathan S. Myers, Murtaza Saifee, William Halfpenny, Keri Dirkes, Linda Zangwill, Kerry E. Goetz, Michelle Hribar, Sally L. Baxter
Language: English
Subfield: Ophthalmology
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $2,500
Awards: Multi-modal Health Information Technology Innovations for Precision Management of Glaucoma, G1610538956, G2161580918, G2366525508, G9000098550, G9000148692, Real-world outcomes of proliferative diabetic retinopathy, Multimodal Artificial Intelligence to Predict Glaucomatous Progression and Surgical Intervention, G927524054
OpenAlex ID: W4402546469