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arXiv Computer Vision By Charis Y. N. Chiang, Tarela Sarimiye, Adeyinka Ashaye, Martin Buist, Michael A. Hauser, Olusola Olawoye, Micha\"el J. A. Girard

Interpretable AI plus Handheld, Portable Retinal Photographs: A Low-Cost Glaucoma Screening Solution for West Africa

Read the original on arXiv Computer Vision →

The study presents an interpretable AI framework for glaucoma screening using low-cost handheld retinal cameras in a West African population. Trained on 681 participants, the system achieved high performance across vessel segmentation, cup/disc segmentation, and optic nerve head feature detection, with classification AUCs of 0.85 for the handheld device and 0.93 for a tabletop camera. The model provides confidence scores and visual explanations to aid clinical interpretation.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Computer Vision.

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