This paper is in the following e-collection/theme issue:

Artificial Intelligence (1773) Clinical Information and Decision Making (1686) New Methods (1035) Decision Support for Health Professionals (1360) Computer-Aided Diagnosis (188) Machine Learning (1769)

Published on in Vol 25 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/48142, first published .
Developing and Evaluating an AI-Based Computer-Aided Diagnosis System for Retinal Disease: Diagnostic Study for Central Serous Chorioretinopathy

Developing and Evaluating an AI-Based Computer-Aided Diagnosis System for Retinal Disease: Diagnostic Study for Central Serous Chorioretinopathy

Developing and Evaluating an AI-Based Computer-Aided Diagnosis System for Retinal Disease: Diagnostic Study for Central Serous Chorioretinopathy

Authors of this article:

Jeewoo Yoon1, 2 Author Orcid Image ;   Jinyoung Han1, 3 Author Orcid Image ;   Junseo Ko1, 2 Author Orcid Image ;   Seong Choi1, 2 Author Orcid Image ;   Ji In Park4 Author Orcid Image ;   Joon Seo Hwang5 Author Orcid Image ;   Jeong Mo Han6 Author Orcid Image ;   Daniel Duck-Jin Hwang7, 8 Author Orcid Image
Article Authors Cited by (2) Tweetations (2) Metrics

Journals

  1. Lin A, Peng Y, Lin T, Dai J, Li J, Shi T, Ke X, Liao X, Fang D, Chen M, Liang H, Chen S, Xia H, Wang J, Jiang Z, Li T, Liang D, Yu S, Luo J, Gao L, Sun D, Tham Y, Chen X, Chen H. Assistance of Artificial Intelligence in Diagnosis of Vitreoretinal Lymphoma on Optical Coherence Tomography. Advanced Intelligent Systems 2025;7(4) View
  2. Bilal H, Keles A, Bendechache M. Advances in disease detection through retinal imaging: A systematic review. Computers in Biology and Medicine 2025;194:110412 View