Published online Feb 28, 2021. doi: 10.35711/aimi.v2.i1.5
Peer-review started: November 28, 2020
First decision: December 18, 2020
Revised: December 31, 2020
Accepted: February 12, 2021
Article in press: February 12, 2021
Published online: February 28, 2021
Core Tip: Artificial intelligence has improved the diagnostic ability in the ophthalmology field, thereby improving patient care. The in-depth image recognition in diabetic retinopathy, retinopathy of prematurity and age-related macular degeneration has helped in early diagnosis and prevention. The detection of visual filed defect even at its minute stage in glaucoma and other ocular conditions has accurately staged the disease with the prediction of its severity. Still, many challenges need to be addressed, such as image incorporation, training sets and the black box dilemma. Nevertheless, despite the existing differences, there is always a chance of improving machines to potentiate their efficacy and standards.