Development and validation of a deep‐learning algorithm for the detection of neovascular age‐related macular degeneration from colour fundus photographs-Reference-Cited by-同舟云学术

Development and validation of a deep‐learning algorithm for the detection of neovascular age‐related macular degeneration from colour fundus photographs

Published:2019-07-25 Issue:8 Volume:47 Page:1009-1018
ISSN:1442-6404
Container-title:Clinical & Experimental Ophthalmology
language:en
Short-container-title:Clin Experiment Ophthalmol

Author:

Keel Stuart¹^ORCID,Li Zhixi²,Scheetz Jane¹^ORCID,Robman Liubov¹³,Phung James³,Makeyeva Galina¹,Aung KhinZaw¹,Liu Chi⁴,Yan Xixi¹,Meng Wei⁴,Guymer Robyn¹,Chang Robert⁵,He Mingguang¹²

Affiliation:

1. Centre for Eye Research Australia, Royal Victorian Eye and Ear HospitalUniversity of Melbourne Melbourne Victoria Australia

2. State Key Laboratory of OphthalmologyZhongshan Ophthalmic Center, Sun Yat‐Sen University Guangzhou China

3. Monash University Melbourne Melbourne Victoria Australia

4. Healgoo Interactive Medical Technology Co. Ltd. Guangzhou China

5. Department of OphthalmologyByers Eye Institute at Stanford University Palo Alto California

Publisher

Wiley

Subject

Ophthalmology

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/ceo.13575

Reference26 articles.

1. Global prevalence of age-related macular degeneration and disease burden projection for 2020 and 2040: a systematic review and meta-analysis

3. Comparing humans and deep learning performance for grading AMD: A study in using universal deep features and transfer learning for automated AMD analysis

4. Automated Grading of Age-Related Macular Degeneration From Color Fundus Images Using Deep Convolutional Neural Networks

5. A Deep Learning Algorithm for Prediction of Age-Related Eye Disease Study Severity Scale for Age-Related Macular Degeneration from Color Fundus Photography

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