Artificial Intelligence to Classify Fundus Photographs of Pediatric Pseudopapilledema and True Papilledema

Update Item Information
Identifier 20230313_nanos_sciplatform1_04
Title Artificial Intelligence to Classify Fundus Photographs of Pediatric Pseudopapilledema and True Papilledema
Creator Melinda Chang; Gena Heidary; Shannon Beres; Stacy Pineles; Eric Gaier; Ryan Gise; Kleanthis Avramidis; Mohammad Rostami; Shrikanth Narayanan
Affiliation (MC) Children's Hospital of Los Angeles, Keck SOM of USC; (GH) (EG) Boston Children's Hospital, Harvard Medical School; (SB) Stanford University; (SP) UCLA; (RG) Boston Children's Hospital; (KA) (MR) (SN) University of Southern California
Subject Pediatric Neuro-ophthalmology
Description Differentiating pseudopapilledema and papilledema in children represents a significant diagnostic dilemma. Although various ophthalmic imaging modalities have been studied, there is no single technique, when interpreted by human observers, that may be relied upon for accurate diagnosis. The purpose of this study was to use artificial intelligence to develop a deep learning model to differentiate pediatric pseudopapilledema and papilledema using fundus photographs.
Date 2023-03
References Chang MY, Binenbaum G, Heidary G, Morrison DG, Galvin JA, et al. Imaging Methods for Differentiating Pediatric Papilledema from Pseudopapilledema: A Report by the American Academy of Ophthalmology. Ophthalmology. 2020 Oct;127(10):1416-1423.
Language eng
Format application/pdf
Format Creation Microsoft PowerPoint
Type Text
Source 2023 North American Neuro-Ophthalmology Society Annual Meeting
Relation is Part of NANOS Annual Meeting 2023: Scientific Platform Session I: https://novel.utah.edu/collection/NAM/toc/
Collection Neuro-Ophthalmology Virtual Education Library: NANOS Annual Meeting Collection: https://novel.utah.edu/collection/nanos-annual-meeting-collection/
Publisher North American Neuro-Ophthalmology Society
Holding Institution Spencer S. Eccles Health Sciences Library, University of Utah
Rights Management Copyright 2023. For further information regarding the rights to this collection, please visit: https://NOVEL.utah.edu/about/copyright
ARK ark:/87278/s63avz18
Setname ehsl_novel_nam
ID 2386541
Reference URL https://collections.lib.utah.edu/ark:/87278/s63avz18
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