Ganglion cell layer analysis with deep learning in glaucoma diagnosis.

Objective: To determine and compare the diagnostic precision in glaucoma of two deep learning models using infrared images of the optic nerve, eye fundus, and the ganglion cell layer (GCL).

Methods: We have selected a sample of normal and glaucoma patients. Three infrared images were registered with a spectral-domain optical coherence tomography (SD-OCT).

Mediterranean diet adherence by patients with primary open angle glaucoma.

Objective: To study the adherence to the Mediterranean diet in patients affected by primary open angle glaucoma (POAG).

Materials And Methods: An observational study was conducted to assess the adherence to the Mediterranean diet in patients affected by POAG, and who attended the Ophthalmology Department of the Canary Islands University Hospital. The study included completing a 14-item questionnaire validated by the PREDIMED Study, in person or by telephone.