Acta Scientific Ophthalmology (ISSN: 2582-3191)

Review Article Volume 8 Issue 2

Artificial Intelligence in Ophthalmology: Revolutionizing Eye Care Through Innovation

Baswati Sahoo*

Clinical Lead, Department of Ophthalmology, Hawkes Bay Fallen Soldiers’ Memorial Hospital, New Zealand

*Corresponding Author: Baswati Sahoo, Clinical Lead, Department of Ophthalmology, Hawkes Bay Fallen Soldiers’ Memorial Hospital, New Zealand.

Received: February 03, 2025; Published: February 11, 2025

Abstract

Artificial Intelligence (AI) is revolutionizing ophthalmology by enhancing early detection, diagnosis, and management of vision-threatening diseases such as diabetic retinopathy, glaucoma, age-related macular degeneration, and cataracts. With over 2.2 billion people affected by vision impairment, AI-driven solutions offer scalable, cost-effective, and accessible eye care, particularly in underserved regions. AI-powered imaging analysis, predictive analytics, and teleophthalmology platforms are improving diagnostic precision and expanding access to care. Furthermore, AI-assisted robotic surgery and personalized treatment strategies are optimizing clinical outcomes. However, challenges such as data bias, regulatory hurdles, privacy concerns, and ethical considerations must be addressed to ensure equitable implementation. While AI will not replace ophthalmologists, it serves as a powerful tool to augment clinical expertise and democratize eye health services. Collaborative efforts among technologists, healthcare professionals, and policymakers are essential for harnessing AI’s full potential in preventing blindness and advancing global eye care.

Keywords: Artificial Intelligence; Robotic Surgery; Revolutionizing Eye Care

References

  1. Xinjia Xu., et al. “The application of artificial intelligence in diabetic retinopathy: progress and prospects”. Frontiers in Cell and Developmental Biology 12 (2024): 1473176.
  2. Yan Q., et al. “Genome-Wide Association Studies-Based Machine Learning for prediction of age-related Macular Degeneration Risk”. Translational Vision Science and Technology2 (2021): 29.
  3. Lee AY., et al. “Exploring a structural basis for delayed rod-mediated Dark Adaptation in Age-Related Macular Degeneration Via Deep Learning”. Translational Vision Science and Technology2 (2020): 62.
  4. Siamak Yousefi. “Clinical Applications of Artificial Intelligence in Glaucoma”. Journal of Ophthalmic and Vision Research 1 (2023): 97-112.
  5. Pragnya Ramjee., et al. “CataractBot: An LLM-Powered Expert-in-the-Loop Chatbot for Cataract Patients”. (2024).

Citation

Citation: Baswati Sahoo. “Artificial Intelligence in Ophthalmology: Revolutionizing Eye Care Through Innovation".Acta Scientific Ophthalmology 8.2 (2025): 18-20.

Copyright

Copyright: © 2025 Baswati Sahoo. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.




Metrics

Acceptance rate35%
Acceptance to publication20-30 days
ISI- IF1.042
JCR- IF0.24

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