The era of artificial intelligence (AI) has revolutionized our daily lives and AI has become a
powerful force that is gradually transforming the field of medicine. Ophthalmology sits at the …

Introduction The steadily growing and aging world population, in conjunction with
continuously increasing prevalences of vision-threatening retinal diseases, is placing an …

Clinical diagnosis of the eye is performed over multifarious data modalities including scalar
clinical labels, vectorized biomarkers, two-dimensional fundus images, and three …

This article presents a novel positive and negative set selection strategy for contrastive
learning of medical images based on labels that can be extracted from clinical data. In the …

Deep learning (DL) is a subset of artificial intelligence based on deep neural networks. It has
made remarkable breakthroughs in medical imaging, particularly for image classification …

Purpose To create a model for prediction of postoperative visual acuity (VA) after vitrectomy
for macular hole (MH) treatment using preoperative optical coherence tomography (OCT) …

Background The efficiency of clinical trials for retinitis pigmentosa (RP) treatment is limited
by the screening burden and lack of reliable surrogate markers for functional end points …

Purpose: To survey the current literature regarding applications of deep learning to optical
coherence tomography in age-related macular degeneration (AMD). Methods: A Preferred …

Importance High myopia is a global concern due to its escalating prevalence and the
potential risk of severe visual impairment caused by pathologic myopia. Using artificial …

Purpose To develop an artificial intelligence (AI) model for estimating best-corrected visual
acuity (BCVA) using horizontal and vertical optical coherence tomography (OCT) scans of …