Assessing the external validity of machine learning-based detection of glaucoma

• Main Authors: Li, Chi, Chua, Jacqueline, Schwarzhans, Florian, Husain, Rahat, Girard, Michaël J. A., Majithia, Shivani, Tham, Yih-Chung, Cheng, Ching-Yu, Aung, Tin, Fischer, Georg, Vass, Clemens, Bujor, Inna, Kwoh, Chee Keong, Popa-Cherecheanu, Alina, Schmetterer, Leopold, Wong, Damon
• Other Authors: School of Computer Science and Engineering
• Format: Article
• Language: English
• Published: 2023
• Subjects: Engineering::Computer science and engineering; Engineering::Bioengineering; Glaucoma; Machine Learning
• Online Access: https://hdl.handle.net/10356/168760
• Institution: Nanyang Technological University

Studies using machine learning (ML) approaches have reported high diagnostic accuracies for glaucoma detection. However, none assessed model performance across ethnicities. The aim of the study is to externally validate ML models for glaucoma detection from optical coherence tomography (OCT) data. W...