PT  - JOURNAL ARTICLE
AU  - Darren Shu Jeng Ting
AU  - Valencia HX Foo
AU  - Lily Wei Yun Yang
AU  - Josh Tjunrong Sia
AU  - Marcus Ang
AU  - Haotian Lin
AU  - James Chodosh
AU  - Jodhbir S Mehta
AU  - Daniel Shu Wei Ting
TI  - Artificial intelligence for anterior segment diseases: Emerging applications in ophthalmology
AID  - 10.1136/bjophthalmol-2019-315651
DP  - 2021 Feb 01
TA  - British Journal of Ophthalmology
PG  - 158--168
VI  - 105
IP  - 2
4099  - http://bjo.bmj.com/content/105/2/158.short
4100  - http://bjo.bmj.com/content/105/2/158.full
SO  - Br J Ophthalmol2021 Feb 01; 105
AB  - 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 ‘intelligent’ 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.