A variety of ethical concerns about artificial intelligence (AI) implementation in healthcare
have emerged as AI becomes increasingly applicable and technologically advanced. The …

The simultaneous maturation of multiple digital and telecommunications technologies in
2020 has created an unprecedented opportunity for ophthalmology to adapt to new models …

The implementation of artificial intelligence (AI) is driving significant transformation inside
the administrative and clinical workflows of healthcare organizations at an accelerated rate …

Importance The development of artificial intelligence (AI) and other machine diagnostic
systems, also known as software as a medical device, and its recent introduction into clinical …

In the presence of the ever-increasing incidence of diabetes mellitus (DM), the prevalence of
diabetic eye disease (DED) is also growing. Despite many improvements in diabetic care …

Retinopathy of prematurity (ROP) is a disease that can cause blindness in premature infants.
It is characterized by immature vascular growth of the retinal blood vessels. However, early …

Objective Health care systems worldwide are challenged to provide adequate care for the
200 million individuals with age-related macular degeneration (AMD). Artificial intelligence …

Introduction Age-related macular degeneration, diabetic retinopathy, and glaucoma are
vision-threatening diseases that are leading causes of vision loss. Many studies have …

Abstract Domain generalization for Diabetic Retinopathy (DR) classification allows a model
to adeptly classify retinal images from previously unseen domains with various imaging …

Objective To develop deep learning methods with high accuracy for segmenting irregular
corneas and detecting the tear fluid reservoir (TFR) boundary under the scleral lens …