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Novel Low-Shot Deep Learning Approach for Retinal Image Classification With Few Examples.

作者信息

Hunt Matthew S, Kihara Yuka, Lee Aaron Y

机构信息

Department of Ophthalmology, School of Medicine, University of Washington, Seattle.

School of Medicine, Washington University, St Louis, Missouri.

出版信息

JAMA Ophthalmol. 2020 Oct 1;138(10):1077-1078. doi: 10.1001/jamaophthalmol.2020.3256.

DOI:10.1001/jamaophthalmol.2020.3256
PMID:32880607
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8168377/
Abstract
摘要

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本文引用的文献

1
Low-Shot Deep Learning of Diabetic Retinopathy With Potential Applications to Address Artificial Intelligence Bias in Retinal Diagnostics and Rare Ophthalmic Diseases.基于少量样本的深度学习在糖尿病视网膜病变中的应用及其对解决视网膜诊断中人工智能偏倚和罕见眼病问题的潜力。
JAMA Ophthalmol. 2020 Oct 1;138(10):1070-1077. doi: 10.1001/jamaophthalmol.2020.3269.
2
Generating retinal flow maps from structural optical coherence tomography with artificial intelligence.利用人工智能从结构光相干断层扫描生成视网膜血流图。
Sci Rep. 2019 Apr 5;9(1):5694. doi: 10.1038/s41598-019-42042-y.
3
Forecasting future Humphrey Visual Fields using deep learning.利用深度学习预测未来 Humphrey 视野。
PLoS One. 2019 Apr 5;14(4):e0214875. doi: 10.1371/journal.pone.0214875. eCollection 2019.
4
Estimating Retinal Sensitivity Using Optical Coherence Tomography With Deep-Learning Algorithms in Macular Telangiectasia Type 2.利用深度学习算法在黄斑毛细血管扩张症 2 型中使用光学相干断层扫描估计视网膜敏感性。
JAMA Netw Open. 2019 Feb 1;2(2):e188029. doi: 10.1001/jamanetworkopen.2018.8029.
5
Development and Validation of a Deep Learning Algorithm for Detection of Diabetic Retinopathy in Retinal Fundus Photographs.深度学习算法在视网膜眼底照片糖尿病视网膜病变检测中的开发与验证。
JAMA. 2016 Dec 13;316(22):2402-2410. doi: 10.1001/jama.2016.17216.