Development and evaluation of multimodal AI for diagnosis and triage of ophthalmic diseases using ChatGPT and anterior segment images: protocol for a two-stage cross-sectional study.

Journal: Frontiers in artificial intelligence
Published Date: Dec 8, 2023

Abstract

INTRODUCTION: Artificial intelligence (AI) technology has made rapid progress for disease diagnosis and triage. In the field of ophthalmic diseases, image-based diagnosis has achieved high accuracy but still encounters limitations due to the lack of medical history. The emergence of ChatGPT enables human-computer interaction, allowing for the development of a multimodal AI system that integrates interactive text and image information.

Authors

  • Zhiyu Peng
    Department of Ophthalmology, Fudan Eye & ENT Hospital, Shanghai, China.
  • Ruiqi Ma
    Department of Ophthalmology, Fudan Eye & ENT Hospital, Shanghai, China.
  • Yihan Zhang
    Department of Ophthalmology, Fudan Eye & ENT Hospital, Shanghai, China.
  • Mingxu Yan
    Department of Ophthalmology, Fudan Eye & ENT Hospital, Shanghai, China.
  • Jie Lu
    Department of Endocrinology and Metabolism, the Affiliated Hospital of Qingdao University, Qingdao, People's Republic of China.
  • Qian Cheng
    Medical Image Processing, Analysis, and Visualization (MIVAP) Lab, School of Electronics and Information Engineering, Soochow University, Suzhou, China.
  • Jingjing Liao
    Medical Image Processing, Analysis, and Visualization (MIVAP) Lab, School of Electronics and Information Engineering, Soochow University, Suzhou, China.
  • Yunqiu Zhang
    School of Public Health, Fudan University, Shanghai, China.
  • Jinghan Wang
    Department of Ophthalmology, Fudan Eye & ENT Hospital, Shanghai, China.
  • Yue Zhao
    The Affiliated Eye Hospital, Nanjing Medical University, Nanjing, China.
  • Jiang Zhu
    Department of Ophthalmology, Suqian First Hospital, Suqian, China.
  • Bing Qin
    Department of Ophthalmology, Suqian First Hospital, Suqian, China.
  • Qin Jiang
    The Affiliated Eye Hospital, Nanjing Medical University, Nanjing, China.
  • Fei Shi
    Medical Image Processing, Analysis, and Visualization (MIVAP) Lab, School of Electronics and Information Engineering, Soochow University, Suzhou, China.
  • Jiang Qian
    Department of Ophthalmology, Fudan Eye & ENT Hospital, Shanghai, China.
  • Xinjian Chen
    Medical Image Processing, Analysis, and Visualization (MIVAP) Lab, School of Electronics and Information Engineering, Soochow University, Suzhou, China.
  • Chen Zhao
    Department of Ophthalmology, Fudan Eye & ENT Hospital, Shanghai, China.

Keywords

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