Real-World Translation of Artificial Intelligence in Neuro-Ophthalmology: The Challenges of Making an Artificial Intelligence System Applicable to Clinical Practice

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Title Real-World Translation of Artificial Intelligence in Neuro-Ophthalmology: The Challenges of Making an Artificial Intelligence System Applicable to Clinical Practice
Creator Anat Bachar Zipori; Cailey I. Kerley; Ainat Klein; Rachel C. Kenney
Affiliation Ophthalmology Department (ABZ, AK), Tel Aviv Medical Center, Tel Aviv, Israel; Sackler Faculty of Medicine (ABZ, AK), Tel Aviv University, Tel Aviv, Israel; Department of Electrical and Computer Engineering (CK, RK), Vanderbilt University, Nashville, Tennessee; and Department of Radiology and Radiological Sciences and Medicine (RK), Vanderbilt University Medical Center, Nashville, Tennessee
Abstract 1. Lin D, Xiong J, Liu C, Zhao L, Li Z, Yu S, Wu X, Ge Z, Hu X, Wang B, Fu M, Zhao X, Wang X, Zhu Y, Chen C, Li T, Li Y, Wei W, Zhao M, Li J, Xu F, Ding L, Tan G, Xiang Y, Hu Y, Zhang P, Han Y, li J, Wei L, Zhu P, Liu Y, Chen W, Ting D, Wong T, Chen Y, Lin H. Application of Comprehensive Artificial intelligence Retinal Expert (CARE) system: a national real-world evidence study. Lancet Digit Health. 2021;3:e486-e495. 2. Xie Y, Nguyen Q, Bellemo V, Yip M, Lee M, Hamzah H, Lim G, Hsu W, Lee ML, Wang JJ, Cheng CY, Finkelstein EA, Lamoureux EL, Tan GSW, Wong T. Cost-Effectiveness analysis of an artificial intelligence-assisted deep learning system implemented in the national tele-medicine diabetic retinopathy screening in Singapore. Invest Ophthalmol Vis Sci. 2019;60:5471. 3. Gulshan V, Peng L, Coram M, Stumpe MC, Wu D, Narayanaswamy A, Venugopalan S, Widner K, Madams T, Cuadros J, Kim R, Raman R, Nelson PC, Mega JL, Webster DR. Development and validation of a deep learning algorithm for detection of diabetic retinopathy in retinal fundus Photographs. JAMA. 2016;316:2402-2410. 4. van der Heijden AA, Abramoff MD, Verbraak F, van Hecke M, Liem A, Nijpels G. Validation of automated screening for referable diabetic retinopathy with the IDx-DR device in the Hoorn Diabetes Care System. Acta Ophthalmol. 2018;96:63-68. 5. Milea D, Najjar RP, Jiang Z, Ting D, Vasseneix C, Xu X, Aghsaei Fard M, Fonseca P, Vanikieti K, Lagrèze WA, La Morgia C, Cheung CY, Hamann S, Chiquet C, Sanda N, Yang H, Mejico LJ, Rougier MB, Kho R, Tran THC, Singhal S, Gohier P, Vignal-Clermont C, Cheng Cy, Jonas JB, Yu-Wai-Man P, Fraser CL, Chen JJ, Ambika S, Miller NR, Liu Y, Newman NJ, Wong TY, Biousse V. Artificial intelligence to detect papilledema from ocular fundus Photographs. New Engl J Med. 2020;382:1687-1695.
Subject Artificial Intelligence; Ophthalmology
OCR Text Show
Date 2022-09
Date Digital 2022-09
Language eng
Format application/pdf
Type Text
Publication Type Journal Article
Source Journal of Neuro-Ophthalmology, September 2022, Volume 42, Issue 3
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/s66b034d
Setname ehsl_novel_jno
ID 2344198
Reference URL https://collections.lib.utah.edu/ark:/87278/s66b034d
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