Clinical evaluation of deep learning systems for assisting in the diagnosis of the epiretinal membrane grade in general ophthalmologists.

Journal: Eye (London, England)
PMID: 37848677

Abstract

BACKGROUND: Epiretinal membrane (ERM) is a common age-related retinal disease detected by optical coherence tomography (OCT), with a prevalence of 34.1% among people over 60 years old. This study aims to develop artificial intelligence (AI) systems to assist in the diagnosis of ERM grade using OCT images and to clinically evaluate the potential benefits and risks of our AI systems with a comparative experiment.

Authors

  • Yan Yan
    Department of Biomedical Engineering, Wayne State University, Detroit, Michigan, USA.
  • Xiaoling Huang
    Department of Ophthalmology, The Second Affiliated Hospital of Zhejiang University, College of Medicine, Hangzhou, 310009, China.
  • Xiaoyu Jiang
    School of Physical Science and Technology, ShanghaiTech University, Shanghai, 201210, China.
  • Zhiyuan Gao
    Department of Ophthalmology, The Second Affiliated Hospital of Zhejiang University, College of Medicine, Hangzhou, Zhejiang, China.
  • Xindi Liu
    Department of Ophthalmology, College of Medicine, The Second Affiliated Hospital of Zhejiang University, Hangzhou, China.
  • Kai Jin
    Eye Center, The Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China.
  • Juan Ye
    Eye Center, The Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China.

Keywords

External Resources

Popular Topics
Recent Journals