Identifier |
20220214_nanos_sciplatform1_07 |
Title |
A Prospective, Clinic-Based Evaluation of a Trained Deep-Learning System Reveals High Accuracy for Papilledema Detection |
Creator |
Raymond Najjar, PhD |
Subject |
High Intracranial Pressure/Headache; Diagnostic Tests (ERG, VER, OCT, HRT, mfERG, etc); Optic Neuropathy; Optic Neuritis; Pseudotumor Cerebri |
Description |
We recently developed a deep-learning system (BONSAI-DLS) to detect papilledema and other optic disk abnormalities on ocular fundus photographs (1). However, this DLS was only validated retrospectively on curated data, limiting its translatability into clinical practice. The aim of this study is to prospectively evaluate the BONSAI-DLS's performance for the detection of papilledema and other disk abnormalities in clinical settings. |
Date |
2022-02 |
Language |
eng |
Format |
application/pdf |
Type |
Text |
Source |
2022 North American Neuro-Ophthalmology Society Annual Meeting |
Relation is Part of |
NANOS Annual Meeting 2022: Scientific Platform Session I |
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 2022. For further information regarding the rights to this collection, please visit: https://NOVEL.utah.edu/about/copyright |
ARK |
ark:/87278/s6yx8yer |
Context URL |
The NANOS Annual Meeting Neuro-Ophthalmology Collection: https://novel.utah.edu/collection/NAM/toc/ |
Contributor Primary |
Raymond Najjar, PhD |
Setname |
ehsl_novel_nam |
ID |
2106492 |
Reference URL |
https://collections.lib.utah.edu/ark:/87278/s6yx8yer |