Prior optic neuritis detection on peripapillary ring scans using deep learning

• Published in: Annals of clinical and translational neurology Vol. 9; no. 11; pp. 1682 - 1691
• Main Authors: Motamedi, Seyedamirhosein, Yadav, Sunil Kumar, Kenney, Rachel C., Lin, Ting‐Yi, Kauer‐Bonin, Josef, Zimmermann, Hanna G., Galetta, Steven L., Balcer, Laura J., Paul, Friedemann, Brandt, Alexander U.
• Format: Journal Article
• Language: English
• Published: United States John Wiley & Sons, Inc 01.11.2022; John Wiley and Sons Inc; Wiley
• Subjects: Age; Artificial intelligence; Biomarkers; Datasets; Deep Learning; Ethnicity; Hispanic Americans; Humans; Longitudinal studies; Multiple sclerosis; Multiple Sclerosis - diagnostic imaging; Neural networks; Optic nerve; Optic Neuritis - diagnostic imaging; Optics; Pacific Islander people; Patients; Retina; Tomography; Tomography, Optical Coherence - methods; White people; New York; United States > US

Background The diagnosis of multiple sclerosis (MS) requires demyelinating events that are disseminated in time and space. Peripapillary retinal nerve fiber layer (pRNFL) thickness as measured by optical coherence tomography (OCT) distinguishes eyes with a prior history of acute optic neuritis (ON)...