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Abstract #94905 Published in IGR 22-2
An Artificial-Intelligence- and Telemedicine-Based Screening Tool to Identify Glaucoma Suspects from Color Fundus Imaging
Bhuiyan A; Govindaiah A; Smith RTJournal of Ophthalmology 2021; 2021: 6694784
RESULTS: The system achieved an accuracy of 89.67% (sensitivity, 83.33%; specificity, 93.89%; and AUC, 0.93). For external validation, the Retinal Fundus Image Database for Glaucoma Analysis dataset, which has 638 gradable quality images, was used. Here, the model achieved an accuracy of 83.54% (sensitivity, 80.11%; specificity, 84.96%; and AUC, 0.85). CONCLUSIONS: Having demonstrated an accurate and fully automated glaucoma-suspect screening system that can be deployed on telemedicine platforms, we plan prospective trials to determine the feasibility of the system in primary-care settings.
Full article
Classification:
1.6 Prevention and screening (Part of: 1 General aspects)
6.8.2 Posterior segment (Part of: 6 Clinical examination methods > 6.8 Photography)
6.19 Telemedicine (Part of: 6 Clinical examination methods)
6.9.5 Other (Part of: 6 Clinical examination methods > 6.9 Computerized image analysis)
