The deep learning system distinguishes IIH, NAION, and healthy eyes with 93.6% accuracy, aiding in resource-limited settings.

In addition, we assessed MOSAIC’s ability to detect keratitis, conjunctivitis, and pterygium using the Union Centers Smartphone ... In contrast to conventional deep learning models for classification ...

The following is a summary of “Performance of artificial intelligence-based models for epiretinal membrane diagnosis: A ...

Artificial Intelligence (AI) increasingly influences daily life, from search engines to hiring processes. However, hidden ...

A new AI-powered tool allows patients to record and upload eye movement videos from home, enabling clinicians to diagnose ...

Combined biomechanical and topographical data from ORA, Corvis ST, and OCT can improve the early detection of keratoconus.

This study aims to develop and validate a mobile health (mHealth) machine learning model to reliably predict blood Hgb and Hct levels in Black African pregnant women using smartphone ... active or ...