Eye health and vision have widespread and profound implications for many aspects of life,
health, sustainable development, and the economy. Yet nowadays, many people, families …

Deep learning (DL) has the potential to transform medical diagnostics. However, the
diagnostic accuracy of DL is uncertain. Our aim was to evaluate the diagnostic accuracy of …

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

The advent of computer graphic processing units, improvement in mathematical models and
availability of big data has allowed artificial intelligence (AI) using machine learning (ML) …

Diabetes is a chronic metabolic disorder that affects an estimated 463 million people
worldwide. Aiming to improve the treatment of people with diabetes, digital health has been …

Background Deep learning is a novel machine learning technique that has been shown to
be as effective as human graders in detecting diabetic retinopathy from fundus photographs …

The ambition of precision medicine is to design and optimize the pathway for diagnosis,
therapeutic intervention, and prognosis by using large multidimensional biological datasets …

Diabetic Retinopathy (DR) is a leading cause of vision loss in the world. In the past few
years, artificial intelligence (AI) based approaches have been used to detect and grade DR …

Background The ophthalmology field was among the first to adopt artificial intelligence (AI)
in medicine. The availability of digitized ocular images and substantial data have made …

Diabetic retinopathy (DR) is a leading cause of blindness globally. There is growing
evidence to support the use of artificial intelligence (AI) in diabetic eye care, particularly for …