The field of artificial intelligence is essentially the use of machines to perform tasks that typically require human intelligence. It encompasses machine learning, where machines can learn by experience and acquire skills without human involvement (deep learning). Artificial intelligence (AI) has become one of the most influential information technology revolutions today. Combined with medicine, AI would make doctor's work more precisely and effectively. In the field of ophthalmology, especially in diseases that cause blindness and diseases with high incidences, AI-assisted medical screening and diagnosis based on images are emerging in various subspecialties.

Diabetic retinopathy (DR) is the leading cause of blindness in working-age people that has gradually been recognised as a global public health problem. AI can be applied to large scale screening of DR to detect potentially threatening changes at early stages which will benefit from treatment and management, based on fundus image and/or CT image analysis. AI-assisted age-related macular degeneration (AMD) screening for elderly people is another emerging application that may reduce the workload of clinicians and improve efficiency. Concerning the field of paediatric ophthalmology, AI could be utilised in screening for retinopathy of prematurity (ROP) and congenital cataracts.

The aim of this Special Issue is to provide a broad overview of the implications and applications of artificial intelligence (AI) in modern ophthalmology clinical practice. Submissions are particularly encouraged that show novel prospective concerning AI in ophthalmology practice and solving medical and diagnostic issues. Current limitations, future innovations, and review articles will also be considered that describe a new era in ophthalmology practice.

Potential topics include but are not limited to the following:

• The implications of AI in modern clinical practice and screening of common ophthalmological health problems
• The sensitivity and accuracy of AI-assisted screening compared to traditional screening
• The limitations of AI applications in current medical practice
• Future prospective of AI in ophthalmology practice