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What is Binocular Machine Learning for Glaucoma Detection about?

This study introduces a multi-modal machine learning approach for early glaucoma diagnosis that utilizes ocular fundus images from both eyes and integrates clinical data. The methodology compares a monocular mode, which analyzes each eye separately, to a binocular mode that combines information from both eyes, achieving improved diagnostic accuracy. Results indicate that the binocular approach, along with clinical data, enhances model performance, achieving an AUC of 0.796 for Gradient-Boosted Decision Tree

Author

Diwan Singh Dahiya

Language

EN