@article {1517168,
	title = {Artificial intelligence for anterior segment diseases: Emerging applications in ophthalmology},
	journal = {Br J Ophthalmol},
	volume = {105},
	number = {2},
	year = {2021},
	month = {2021 Feb},
	pages = {158-168},
	abstract = {With the advancement of computational power, refinement of learning algorithms and architectures, and availability of big data, artificial intelligence (AI) technology, particularly with machine learning and deep learning, is paving the way for {\textquoteright}intelligent{\textquoteright} healthcare systems. AI-related research in ophthalmology previously focused on the screening and diagnosis of posterior segment diseases, particularly diabetic retinopathy, age-related macular degeneration and glaucoma. There is now emerging evidence demonstrating the application of AI to the diagnosis and management of a variety of anterior segment conditions. In this review, we provide an overview of AI applications to the anterior segment addressing keratoconus, infectious keratitis, refractive surgery, corneal transplant, adult and paediatric cataracts, angle-closure glaucoma and iris tumour, and highlight important clinical considerations for adoption of AI technologies, potential integration with telemedicine and future directions.},
	issn = {1468-2079},
	doi = {10.1136/bjophthalmol-2019-315651},
	author = {Ting, Darren Shu Jeng and Foo, Valencia Hx and Yang, Lily Wei Yun and Sia, Josh Tjunrong and Ang, Marcus and Lin, Haotian and Chodosh, James and Mehta, Jodhbir S and Ting, Daniel Shu Wei}
}
