AI Medical Compendium Journal:
Seminars in ophthalmology

Showing 11 to 16 of 16 articles

Artificial Intelligence in the assessment of diabetic retinopathy from fundus photographs.

Seminars in ophthalmology
: Over the next 25 years, the global prevalence of diabetes is expected to grow to affect 700 million individuals. Consequently, an unprecedented number of patients will be at risk for vision loss from diabetic eye disease. This demand will almost ce...

Advances in Telemedicine in Ophthalmology.

Seminars in ophthalmology
Telemedicine is the provision of healthcare-related services from a distance and is poised to move healthcare from the physician's office back into the patient's home. The field of ophthalmology is often at the forefront of technological advances in ...

Diabetic retinopathy and ultrawide field imaging.

Seminars in ophthalmology
The introduction of ultrawide field imaging has allowed the visualization of approximately 82% of the total retinal area compared to only 30% using 7-standard field Early Treatment Diabetic Retinopathy (ETDRS) photography. This substantially wider fi...

A Review of Machine Learning Techniques for Keratoconus Detection and Refractive Surgery Screening.

Seminars in ophthalmology
Various machine learning techniques have been developed for keratoconus detection and refractive surgery screening. These techniques utilize inputs from a range of corneal imaging devices and are built with automated decision trees, support vector ma...

Machine Learning in the Detection of the Glaucomatous Disc and Visual Field.

Seminars in ophthalmology
Glaucoma is the leading cause of irreversible blindness worldwide. Early detection is of utmost importance as there is abundant evidence that early treatment prevents disease progression, preserves vision, and improves patients' long-term quality of ...

Introduction to Machine Learning for Ophthalmologists.

Seminars in ophthalmology
New diagnostic and imaging techniques generate such an incredible amount of data that it is often a challenge to extract all information that could be possibly useful in clinical practice. Machine Learning techniques emerged as an objective tool to a...