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Li Zhidong

๐Ÿ‡ข๐Ÿ‡ญ Sun Yat-sen University
ORCIDOpenAlex9 articles in GJC

9 articles in GJC

5.

Detecting Glaucoma in Highly Myopic Eyes From Fundus Photographs Using Deep Convolutional Neural Networks.

Chen Xiaohong, Zhou Chen, Zhu Yingting, Luo Man, Hu Lingjing, Han Wenjing et al.

Clin Exp OphthalmolFeb 20252 citationsObservational Study

A deep learning model accurately detected glaucoma in highly myopic eyes from fundus photos (97.7% accuracy), outperforming ophthalmologists and identifying specific diagnostic features, offering significant clinical diagnostic assistance.

6.

Age-period-cohort analysis of the global burden of visual impairment according to major causes: an analysis of the Global Burden of Disease Study 2019.

Chen Jianqi, Zhu Yingting, Li Zhidong, Zhuo Xiaohua, Zhang Shaochong, Zhuo Yehong

Br J OphthalmolOct 20249 citationsCohort Study

This study analyzed global visual impairment trends from cataract, glaucoma, and AMD. Glaucoma/AMD prevalence declined globally, but cataract rose. Heterogeneity across regions highlights varied vision health and treatment priorities.

7.

Quantitative Assessment of Fundus Tessellated Density in Highly Myopic Glaucoma Using Deep Learning.

Chen Xiaohong, Chen Xuhao, Chen Jianqi, Li Zhidong, Huang Shaofen, Shen Xinyue et al.

Transl Vis Sci TechnolApr 20246 citationsCross-Sectional Study

Deep learning quantified fundus tessellated density in highly myopic glaucoma (HMG) versus high myopia (HM). HMG showed distinct FTD patterns, particularly a higher macular nasal/temporal ratio, offering a potential diagnostic marker for early HMG detection.

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