1. The Role of OCT Criteria and Machine Learning in Multiple Sclerosis and Optic Neuritis Diagnosis

    The Role of OCT Criteria and Machine Learning in Multiple Sclerosis and Optic Neuritis Diagnosis

    Background and objectives: Recent studies have suggested that inter-eye differences (IEDs) in peripapillary retinal nerve fiber layer (pRNFL) or ganglion cell+inner plexiform (GCIPL) thickness by spectral-domain optical coherence tomography (SD-OCT) may identify people with a history of unilateral optic neuritis (ON). However, this requires further validation. Machine learning classification may be useful for validating thresholds for OCT IEDs and for examining added utility for visual function tests, such as low-contrast letter acuity (LCLA), in the diagnosis of people with multiple sclerosis (PwMS) and for unilateral ON history. Methods: Participants were from 11 sites within the International Multiple Sclerosis Visual ...

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