Open Daily: 10am - 10pm | Alley door pickup 10am - 7pm 3038 Hennepin Ave Minneapolis, MN
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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
AI in Modern Ophthalmology: Revolutionizing Eye Care with Machine Learning, and Deep Learning

AI in Modern Ophthalmology: Revolutionizing Eye Care with Machine Learning, and Deep Learning

Komolafe, Temitope Emmanuel
Jeevakumari S., Jenifer
K, Manimala

Hardcover

Series: Analytics and AI for Healthcare

General Computers

PREORDER - Expected ship date December 24, 2026

ISBN10: 1041304749
ISBN13: 9781041304746
Publisher: CRC Press
Published: Dec 24 2026
Pages: 212
Language: English

The book provides an authoritative and accessible guide on integrating intelligent technologies, specifically Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL), into modern eye care.

Written by experts in ophthalmology, medical AI, and healthcare innovation, it offers a multidisciplinary exploration of how these tools are fundamentally redefining ophthalmic diagnostics, therapeutics, and surgical interventions. The core focus is on bridging the gap between technical AI innovations and their clinical deployment, offering a practical roadmap for clinicians and researchers. It combines cutting-edge research with real-world applications to demonstrate how AI is being used for the early and accurate detection of retinal diseases and glaucoma, enhancing surgical precision via robotics, and guiding personalized treatment plans. Three key areas are studied throughout the book. First, AI-powered imaging diagnostics, to explore how ML and DL models are used for the early and accurate detection of retinal diseases and glaucoma, supporting faster and more precise decision-making. Second, the application of AI-assisted surgical robotics in ophthalmology: In this topic, we shall examine how AI integration in robotic surgery enhances precision, reduces risk, and supports surgical planning. Third, ethical and regulatory considerations to address the responsible adoption of AI, including data governance, patient privacy, and health equity in ophthalmic care. These topics are essential for stakeholders navigating the clinical, technical, and ethical dimensions of AI implementation and adoption. Ultimately, the text aims to show how the responsible adoption of AI is actively improving clinical outcomes and reshaping the future of vision science.

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