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- Reviews current and predicted trends
- Written by world leading experts in the field
- Assesses how AI can be applied in ophthalmic healthcare
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. Table of Contents- Artificial Intelligence in Ophthalmology: Promises, Hazards and Challenges
- Basics of Artificial Intelligence for Ophthalmologists
- Overview of Artificial Intelligence Systems in Ophthalmology
- Autonomous Artificial Intelligence Safety and Trust
- Technical Aspects of Deep Learning in Ophthalmology
- Selected Image Analysis Methods for Ophthalmology
- Experimental Artificial Intelligence Systems in Ophthalmology: An Overview
- Artificial Intelligence in Age-Related Macular Degeneration (AMD)
- AI and Glaucoma
- Artificial Intelligence in Retinopathy of Prematurity
- Artificial Intelligence in Diabetic Retinopathy
- Google and DeepMind: Deep Learning Systems in Ophthalmology
- Singapore Eye Lesions Analyzer (SELENA): The Deep Learning System for Retinal Diseases
- Automatic Retinal Imaging and Analysis: Age-Related Macular Degeneration (AMD) within Age-Related Eye Disease Studies (AREDS)
- Artificial Intelligence for Keratoconus Detection and Refractive Surgery Screening
- Artificial Intelligence for Cataract Management
- Artificial Intelligence in Refractive Surgery
- Artificial Intelligence in Cataract Surgery Training
- Artificial Intelligence in Ophthalmology Triaging
- Deep Learning Applications in Ocular Oncology
- Artificial Intelligence in Neuro-ophthalmology
- Artificial Intelligence Using the Eye as a Biomarker of Systemic Risk
- Artificial Intelligence in Calculating the IOL Power
- Practical Considerations for AI Implementation in IOL Calculation Formulas
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