• Kanchalika Sathianvichitr, Oriana Lamoureux, Sakura Nakada, Zhiqun Tang, Leopold Schmetterer, Christopher Chen, Carol Y Cheung, Raymond P Najjar, and Dan Milea.
• Visual Neurosciences Research Group, Singapore Eye Research Institute, Singapore National Eye Centre, Singapore.
• Ann Acad Med Singap. 2023 Feb 1; 52 (2): 889588-95.

IntroductionDetection of neurological conditions is of high importance in the current context of increasingly ageing populations. Imaging of the retina and the optic nerve head represents a unique opportunity to detect brain diseases, but requires specific human expertise. We review the current outcomes of artificial intelligence (AI) methods applied to retinal imaging for the detection of neurological and neuro-ophthalmic conditions.MethodCurrent and emerging concepts related to the detection of neurological conditions, using AI-based investigations of the retina in patients with brain disease were examined and summarised.ResultsPapilloedema due to intracranial hypertension can be accurately identified with deep learning on standard retinal imaging at a human expert level. Emerging studies suggest that patients with Alzheimer's disease can be discriminated from cognitively normal individuals, using AI applied to retinal images.ConclusionRecent AI-based systems dedicated to scalable retinal imaging have opened new perspectives for the detection of brain conditions directly or indirectly affecting retinal structures. However, further validation and implementation studies are required to better understand their potential value in clinical practice.

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