The use of artificial intelligence (AI) in medicine is beginning to alter current procedures in
prevention, diagnosis, treatment, amelioration, cure of disease and other physical and …

Artificial intelligence (AI) is gradually changing medical practice. With recent progress in
digitized data acquisition, machine learning and computing infrastructure, AI applications …

A number of large technology companies have created code-free cloud-based platforms that
allow researchers and clinicians without coding experience to create deep learning …

Automated retinal image analysis holds prime significance in the accurate diagnosis of
various critical eye diseases that include diabetic retinopathy (DR), age-related macular …

The incidence of retinopathy of prematurity (ROP) continues to rise due to the improved
survival of very low birth weight infants in developed countries. This epidemic is also fueled …

Over the last few years, a couple of smartphones with different analytical methods have
been applied as efficient, compact, emergence and cost effective devices for on-site …

Retinal imaging technology is rapidly advancing and can provide ever-increasing amounts
of information about the structure, function and molecular composition of retinal tissue in …

The global burden of diabetes has resulted in an increase in the prevalence of diabetic
retinopathy (DR), a microvascular complication of diabetes. Lifelong repetitive screening for …

In clinical ophthalmology, a variety of image-related diagnostic techniques have begun to
offer unprecedented insights into eye diseases based on morphological datasets with …

The blood vessels are the primary anatomical structure that can be visible in retinal images.
The segmentation of retinal blood vessels has been accepted worldwide for the diagnosis of …