{"title":"Retinal imaging and artificial intelligence analysis.","authors":"James P Winebrake, Jennifer I Lim","doi":"10.1016/B978-0-443-22212-2.00011-2","DOIUrl":null,"url":null,"abstract":"<p><p>The retina, uniquely accessible as an extension of the central nervous system, plays a critical role in neurology and ophthalmology. Advances in retinal imaging technologies - including color fundus photography, optical coherence tomography, and OCT angiography - have enabled detailed, noninvasive assessment of ocular and systemic diseases. Artificial intelligence (AI), particularly deep learning, has revolutionized the analysis of these images, facilitating early detection, classification, and prognostication of conditions such as diabetic retinopathy, age-related macular degeneration, optic neuropathies, and inherited retinal diseases. AI applications extend beyond ophthalmology, offering insights into neurologic and cerebrovascular disorders through retinal biomarkers. However, challenges remain regarding dataset bias, generalizability, ethical concerns, and the \"black box\" nature of AI models. Addressing these limitations, along with integrating multimodal imaging and fostering cross-specialty collaboration, will be pivotal in ensuring that AI technology is adopted effectively and responsibly. The future will be marked by synergistic AI-human workflows to enhance diagnostic accuracy, screening scalability, and personalized patient care. As AI applications evolve, they promise to reshape retinal imaging and its intersection with neurology, expanding opportunities for early intervention and improved outcomes.</p>","PeriodicalId":12907,"journal":{"name":"Handbook of clinical neurology","volume":"218 ","pages":"3-12"},"PeriodicalIF":0.0000,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Handbook of clinical neurology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1016/B978-0-443-22212-2.00011-2","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"Medicine","Score":null,"Total":0}
引用次数: 0
Abstract
The retina, uniquely accessible as an extension of the central nervous system, plays a critical role in neurology and ophthalmology. Advances in retinal imaging technologies - including color fundus photography, optical coherence tomography, and OCT angiography - have enabled detailed, noninvasive assessment of ocular and systemic diseases. Artificial intelligence (AI), particularly deep learning, has revolutionized the analysis of these images, facilitating early detection, classification, and prognostication of conditions such as diabetic retinopathy, age-related macular degeneration, optic neuropathies, and inherited retinal diseases. AI applications extend beyond ophthalmology, offering insights into neurologic and cerebrovascular disorders through retinal biomarkers. However, challenges remain regarding dataset bias, generalizability, ethical concerns, and the "black box" nature of AI models. Addressing these limitations, along with integrating multimodal imaging and fostering cross-specialty collaboration, will be pivotal in ensuring that AI technology is adopted effectively and responsibly. The future will be marked by synergistic AI-human workflows to enhance diagnostic accuracy, screening scalability, and personalized patient care. As AI applications evolve, they promise to reshape retinal imaging and its intersection with neurology, expanding opportunities for early intervention and improved outcomes.
期刊介绍：
The Handbook of Clinical Neurology (HCN) was originally conceived and edited by Pierre Vinken and George Bruyn as a prestigious, multivolume reference work that would cover all the disorders encountered by clinicians and researchers engaged in neurology and allied fields. The first series of the Handbook (Volumes 1-44) was published between 1968 and 1982 and was followed by a second series (Volumes 45-78), guided by the same editors, which concluded in 2002. By that time, the Handbook had come to represent one of the largest scientific works ever published. In 2002, Professors Michael J. Aminoff, François Boller, and Dick F. Swaab took on the responsibility of supervising the third (current) series, the first volumes of which published in 2003. They have designed this series to encompass both clinical neurology and also the basic and clinical neurosciences that are its underpinning. Given the enormity and complexity of the accumulating literature, it is almost impossible to keep abreast of developments in the field, thus providing the raison d''être for the series. The series will thus appeal to clinicians and investigators alike, providing to each an added dimension. Now, more than 140 volumes after it began, the Handbook of Clinical Neurology series has an unparalleled reputation for providing the latest information on fundamental research on the operation of the nervous system in health and disease, comprehensive clinical information on neurological and related disorders, and up-to-date treatment protocols.
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