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Artificial intelligence in ophthalmology

Edited by: Prof Jianhua Wang

In the ophthalmology, it has been demonstrated that deep learning plays a role in advancing our knowledge and diagnosis of eye diseases. Artificaial interligence models appear to provide solutions to tackle the durden in disease screening, early diagnosis and individualized comprehensive management of these sight-threatening diseases, such as diabetic retinopathy and glaucoma. This thematic series focuses on the recent applications of artificial intelligence in ophthalmology. It aims to publish review articles and original research of the latest discovery in the field. 

This series was published in Eye and Vision.

  1. Axial myopia is the most common type of myopia. However, due to the high incidence of myopia in Chinese children, few studies estimating the physiological elongation of the ocular axial length (AL), which does...

    Authors: Tao Tang, Zekuan Yu, Qiong Xu, Zisu Peng, Yuzhuo Fan, Kai Wang, Qiushi Ren, Jia Qu and Mingwei Zhao
    Citation: Eye and Vision 2020 7:50
    Content type: Research Published on:

  2. To develop an automated classification system using a machine learning classifier to distinguish clinically unaffected eyes in patients with keratoconus from a normal control population based on a combination ...

    Authors: Ce Shi, Mengyi Wang, Tiantian Zhu, Ying Zhang, Yufeng Ye, Jun Jiang, Sisi Chen, Fan Lu and Meixiao Shen
    Citation: Eye and Vision 2020 7:48
    Content type: Research Published on:

  3. The goal was to characterize retinal vasculature by quantitative analysis of arteriole-to-venule (A/V) ratio and vessel density in fundus photos taken with the PanOptic iExaminer System.

    Authors: Huiling Hu, Haicheng Wei, Mingxia Xiao, Liqiong Jiang, Huijuan Wang, Hong Jiang, Tatjana Rundek and Jianhua Wang
    Citation: Eye and Vision 2020 7:46
    Content type: Research Published on:

  4. To describe the diagnostic performance of a deep learning algorithm in discriminating early-stage Fuchs’ endothelial corneal dystrophy (FECD) without clinically evident corneal edema from healthy and late-stag...

    Authors: Taher Eleiwa, Amr Elsawy, Eyüp Özcan and Mohamed Abou Shousha
    Citation: Eye and Vision 2020 7:44
    Content type: Research Published on:

  6. To develop and validate a deep learning-based approach to the fully-automated analysis of macaque corneal sub-basal nerves using in vivo confocal microscopy (IVCM).

    Authors: Jonathan D. Oakley, Daniel B. Russakoff, Megan E. McCarron, Rachel L. Weinberg, Jessica M. Izzi, Stuti L. Misra, Charles N. McGhee and Joseph L. Mankowski
    Citation: Eye and Vision 2020 7:27
    Content type: Research Published on:

  8. Effective screening is a desirable method for the early detection and successful treatment for diabetic retinopathy, and fundus photography is currently the dominant medium for retinal imaging due to its conve...

    Authors: Gilbert Lim, Valentina Bellemo, Yuchen Xie, Xin Q. Lee, Michelle Y. T. Yip and Daniel S. W. Ting
    Citation: Eye and Vision 2020 7:21
    Content type: Review Published on: