Evaluating the accuracy of the Ophthalmologist Robot for multiple blindness-causing eye diseases: a multicentre, prospective study protocol.

Journal: BMJ open
PMID: 38431298

Abstract

INTRODUCTION: Early eye screening and treatment can reduce the incidence of blindness by detecting and addressing eye diseases at an early stage. The Ophthalmologist Robot is an automated device that can simultaneously capture ocular surface and fundus images without the need for ophthalmologists, making it highly suitable for primary application. However, the accuracy of the device's screening capabilities requires further validation. This study aims to evaluate and compare the screening accuracies of ophthalmologists and deep learning models using images captured by the Ophthalmologist Robot, in order to identify a screening method that is both highly accurate and cost-effective. Our findings may provide valuable insights into the potential applications of remote eye screening.

Authors

  • Qixin Li
    National Clinical Research Center for Ocular Diseases, Eye Hospital, Wenzhou Medical University, Wenzhou 325027, China.
  • Jie Tan
    Department of Molecular and Systems Biology, Geisel School of Medicine at Dartmouth, Hanover, NH, USA.
  • He Xie
  • Xiaoyu Zhang
    First Department of Infectious Diseases, The First Affiliated Hospital of China Medical University, Shenyang, China.
  • Qi Dai
    The First Clinical Medical College, Guangxi University of Chinese Medicine, Nanning 530001, China.
  • Zhongwen Li
    Ningbo Key Laboratory of Medical Research on Blinding Eye Diseases, Ningbo Eye Institute, Ningbo Eye Hospital, Wenzhou Medical University, Ningbo, China.
  • Lijing L Yan
    Global Health Research Center, Duke Kunshan University, Kunshan, China chenweimd@wmu.edu.cn lijing.yan@dukekunshan.edu.cn.
  • Wei Chen
    Department of Urology, Zigong Fourth People's Hospital, Sichuan, China.

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