Artificial Intelligence Reveals Disease-Specific Quantifiable Visual Field Defects in Idiopathic Intracranial Hypertension

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Identifier 20210221_nanos_journalclub1_03-video
Title Artificial Intelligence Reveals Disease-Specific Quantifiable Visual Field Defects in Idiopathic Intracranial Hypertension
Creator Hiten Doshi, Elena Solli, Louis Pasquale, Tobias Elze, Michael Wall, Mark Kupersmith
Subject Optic Neuropathy; Pseudotumor Cerebri; Visual Fields
Description Assessing regional visual field (VF) changes typically requires qualitative expert or subjective analysis. Archetypal analysis (AA), a type of unsupervised machine learning, has been used to identify and monitor patterns of VF loss in glaucoma. AA has not beenapplied to non-glaucomatous optic neuropathy VFs. We investigated the use of AA to quantify and monitor disease-specific VF defects in patients with idiopathic intracranial hypertension (IIH).
Date 2021-02
Language eng
Format video/mp4
Type Image/MovingImage
Source 2021 North American Neuro-Ophthalmology Society Annual Meeting
Relation is Part of NANOS Annual Meeting 2021: Journal Club: What You Need to Know Now!
Collection Neuro-ophthalmology Virtual Education Library: NOVEL http://NOVEL.utah.edu
Publisher Spencer S. Eccles Health Sciences Library, University of Utah
Holding Institution North American Neuro-Ophthalmology Association. NANOS Executive Office 5841 Cedar Lake Road, Suite 204, Minneapolis, MN 55416
Rights Management Copyright 2021. For further information regarding the rights to this collection, please visit: https://NOVEL.utah.edu/about/copyright
ARK ark:/87278/s6868fz1
Context URL The NANOS Annual Meeting Neuro-Ophthalmology Collection: https://novel.utah.edu/collection/NAM/toc/
Contributor Primary Hiten A. Doshi, BS
Contributor Secondary Elena Solli, Louis Pasquale, Tobias Elze, Michael Wall, Mark Kupersmith
Setname ehsl_novel_nam
ID 1698234
Reference URL https://collections.lib.utah.edu/ark:/87278/s6868fz1
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