A Step Forward in Using Artificial Intelligence to Identify Serious Retinopathy of Prematurity—A Start With a Long Road Ahead
Author:
Affiliation:
1. Division of Ophthalmology, The Children’s Hospital of Philadelphia, University of Pennsylvania, Philadelphia
Publisher
American Medical Association (AMA)
Subject
General Medicine
Link
https://jamanetwork.com/journals/jamanetworkopen/articlepdf/2779459/quinn_2021_ic_210083_1619553970.67991.pdf
Reference6 articles.
1. Automated explainable multidimensional deep learning platform of retinal images for retinopathy of prematurity screening.;Wang;JAMA Netw Open,2021
2. The International Classification of Retinopathy of Prematurity revisited.;International Committee for the Classification of Retinopathy of Prematurity;Arch Ophthalmol,2005
3. Vitreous hemorrhage in patients with high-risk retinopathy of prematurity.;Hutcheson;Am J Ophthalmol,2003
4. Intraocular hemorrhages and retinopathy of prematurity in the telemedicine approaches to Evaluating Acute-Phase Retinopathy of Prematurity (e-ROP) Study.;Daniel;Ophthalmology,2017
5. Optical coherence tomography in retinopathy of prematurity: looking beyond the vessels.;Maldonado;Clin Perinatol,2013
Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. Application of Artificial Intelligence in the Early Detection of Retinopathy of Prematurity: Review of the Literature;Neonatology;2023
2. Smartphone Telemedicine Networks for Retinopathy of Prematurity (ROP) in Latin America;Digital Eye Care and Teleophthalmology;2023
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