TY - JOUR T1 - Artificial intelligence for anterior segment diseases: Emerging applications in ophthalmology JF - British Journal of Ophthalmology JO - Br J Ophthalmol DO - 10.1136/bjophthalmol-2019-315651 SP - bjophthalmol-2019-315651 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 Y1 - 2020/06/12 UR - http://bjo.bmj.com/content/early/2020/06/22/bjophthalmol-2019-315651.abstract N2 - 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. ER -