Big Data in Neuro-Ophthalmology: International Classification of Diseases Codes

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Title Big Data in Neuro-Ophthalmology: International Classification of Diseases Codes
Creator Leanne Stunkel, MD
Affiliation John F. Hardesty, MD Department of Ophthalmology and Visual Sciences, Washington University in St. Louis, St. Louis, Missouri; and Department of Neurology, Washington University in St. Louis, St. Louis, Missouri
Abstract Advancements in technology, including the widespread adoption of electronic medical record keeping, expanding access to imaging techniques such as nonmydriatic fundus photography the expansion of telemedicine, and the application of artificial intelligence to the field of medicine, promise to revolutionize our ability to diagnose and treat neuro-ophthalmic disease. 'Big data,' for our purposes referring to the dramatic increase in the amount of medical data accessible to researchers, has the potential to accelerate investigations into diagnosis and treatment of neuro-ophthalmic conditions. Meanwhile, machine learning may provide a feasible avenue for analyzing an ever-increasing volume of data.
Subject Nonmydriatic Fundus; Machine Learning
OCR Text Show
Date 2022-03
Language eng
Format application/pdf
Type Text
Publication Type Journal Article
Source Journal of Neuro-Ophthalmology, March 2022, Volume 42, Issue 1
Collection Neuro-Ophthalmology Virtual Education Library: Journal of Neuro-Ophthalmology Archives: https://novel.utah.edu/jno/
Publisher Lippincott, Williams & Wilkins
Holding Institution Spencer S. Eccles Health Sciences Library, University of Utah
Rights Management © North American Neuro-Ophthalmology Society
ARK ark:/87278/s68q0ccf
Setname ehsl_novel_jno
ID 2197437
Reference URL https://collections.lib.utah.edu/ark:/87278/s68q0ccf
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