This book provides a wide-ranging overview of artificial intelligence (AI), machine learning (ML) and deep learning (DL) algorithms in ophthalmology. Expertly written chapters examine AI in age-related macular degeneration, glaucoma, retinopathy of prematurity and diabetic retinopathy screening. AI perspectives, systems and limitations are all carefully assessed throughout the book as well as the technical aspects of DL systems for retinal diseases including the application of Google DeepMind, the Singapore algorithm, and the Johns Hopkins algorithm.

Artificial Intelligence in Ophthalmology meets the need for a resource that reviews the benefits and pitfalls of AI, ML and DL in ophthalmology. Ophthalmologists, optometrists, eye-care workers, neurologists, cardiologists, internal medicine specialists, AI engineers and IT specialists with an interest in how AI can help with early diagnosis and monitoring treatment in ophthalmic patients will find this book to be an indispensable guide to an evolving area of healthcare technology.

Artificial intelligence in Medicine

Artificial intelligence in AMD
Artificial intelligence in Glaucoma
Artificial intelligence in Retinopathy of Prematurity
Artificial intelligence in Diabetic Retinopathy Screening
The overview of available artificial intelligence systems in Ophthalmology
The overview of experimental artificial intelligence systems in Ophthalmology
Technical aspects of deep learning in Ophthalmology
Deep learning systems for retinal diseases
Google DeepMind
Singapore algorithm
Johns Hopkins algorithm
Perspectives of artificial intelligence in Ophthalmology
Limitations of artificial intelligence in Ophthalmology
Artificial intelligence in calculating the IOL power.