Journals / International Anatolia Academic Online Journal Health Sciences / 2026 / Cilt: 12 Sayı: 1

THE ROLE OF AI TECHNOLOGIES IN TRANSFORMING OPHTHALMOLOGY AND OPHTHALMIC SURGERY

YAPAY ZEKA TEKNOLOJILERININ OFTALMOLOJI VE OFTALMOLOJI CERRAHISINI DÖNÜŞTÜRMEDEKI ROLÜ

Pages
784–792
Publication Date
2026-02-15
DOI
—
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

The convergence of AI with robotic surgery and pharmacological therapies is poised to create innovative solutions for managing complex ophthalmic conditions.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Purpose: Artificial intelligence (AI) is revolutionizing ophthalmology and ophthalmic surgery through enhanced precision in diagnosis, treatment planning, and surgical techniques.
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Key Findings & Data:Relevant case studies are showcased to illustrate the advancements and transformative potential of AI technologies in this field.
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Conclusion & Impact:The convergence of AI with robotic surgery and pharmacological therapies is poised to create innovative solutions for managing complex ophthalmic conditions.
🔬Design:Review & Systematic Survey
📍Scope:Comprehensive Sample
⚙️Variables:YZ oftalmolojisi · robotik cerrahi · ilaç keşfi

Abstract

Purpose: Artificial intelligence (AI) is revolutionizing ophthalmology and ophthalmic surgery through enhanced precision in diagnosis, treatment planning, and surgical techniques. This review discusses how AI serves as a critical tool in drug development, robotic surgery, and personalized medicine for ocular diseases, emphasizing itspotential to improve patient outcomes. Design/Methodology/Approach: The manuscript systematically reviews recent literature on the applications of AI in ophthalmology, including drug discovery, robotic surgical systems, and the integration of organ-on-chip technologies. Relevant case studies are showcased to illustrate the advancements and transformative potential of AI technologies in this field. Findings: AI technologies significantly enhance the accuracy of diagnoses, optimize drug development for ocular diseases, and improve surgical outcomes in ophthalmic procedures. The convergence of AI with robotic surgery and pharmacological therapies is poised to create innovative solutions for managing complex ophthalmic conditions.

Özet

Amaç: Yapay zekâ (YZ), tanı, tedavi planlaması ve cerrahi tekniklerdeki hassasiyeti artırarak oftalmoloji ve oftalmik cerrahide devrim yaratmaktadır. Bu derleme, YZ'nin ilaç geliştirme, robotik cerrahi ve göz hastalıkları için kişiselleştirilmiş tıpta nasıl kritik bir araç olarak hizmet ettiğini ve hasta sonuçlarını iyileştirme potansiyelini vurgulamaktadır. Tasarım/Yöntem: Bu makale, ilaç keşfi, robotik cerrahi sistemler ve organ-on-chip teknolojilerinin entegrasyonu da dahil olmak üzere, oftalmolojide YZ uygulamaları üzerine son literatürü sistematik olarak incelemektedir. Bu alanda YZ teknolojilerinin ilerlemelerini ve dönüştürücü potansiyelini göstermek için ilgili vaka çalışmaları sunulmuştur. Bulgular: YZ teknolojileri, tanı doğruluğunu önemli ölçüde artırır, göz hastalıkları için ilaç geliştirmeyi optimize eder ve oftalmik prosedürlerde cerrahi sonuçları iyileştirir. YZ'nin robotik cerrahi ve farmakolojik tedavilerle birleşmesi, karmaşık oftalmik durumların yönetimi için yenilikçi çözümler yaratmaya hazırdır.

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Cite This Article

Karaarslan, C. (2026). THE ROLE OF AI TECHNOLOGIES IN TRANSFORMING OPHTHALMOLOGY AND OPHTHALMIC SURGERY. International Anatolia Academic Online Journal Health Sciences, Cilt: 12 Sayı: 1, 784–792. https://ajindex.com/articles/1492841

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References (41)

  1. Wu J, et al. Artificial intelligence technology in ophthalmology public health. Transl Vis Sci Technol. 2025;14(5):12-28.
  2. Li Z, et al. AI in ophthalmology: The path to the real-world clinic. Cell Rep Med. 2023;4(7):101095.
  3. Al-Aswad LA, et al. Enhancing Ophthalmic Diagnosis and Treatment with AI. Healthcare (Basel). 2024;12(4):433.
  4. Cheng H, et al. AI for ophthalmic drug discovery. Adv Intell Healthc. 2023;1(3):112-124.
  5. Smith BR, et al. Ophthalmic drug discovery using AI. Nat Rev Drug Discov. 2025;24(2):95-108.
  6. Paul D, et al. AI in drug discovery and development. Drug Discov Today. 2021;26(1):80-93.
  7. Wu K, et al. Machine learning scoring function for drug leads. J Chem Inf Model. 2020;60(4):1643-1651.
  8. Raza MA, et al. AI Applications in Personalized Medicine. Life (Basel). 2024;14(2):204.
  9. Yang S, et al. AI and ML in adverse drug reactions. Artif Intell Chem. 2023;1(2):100011.
  10. Remtulla R, et al. Predicting neuroprotective compounds. Molecules. 2021;26(9):2505.
  11. Sahoo BM, et al. Modern Drug Discovery and Development. Curr Pharm Des. 2023;29(14):1108-1121.
  12. Sharma K, et al. Eye on-chip for drug discovery. Int J Technol. 2024;14(2):125-134.
  13. Deng S, et al. Organ-on-a-chip meets AI in drug evaluation. Theranostics. 2023;13(13):4526-4558.
  14. Zhang L, et al. Quantitative structure-permeability in ocular delivery. Mol Pharmaceut. 2020;17(10):4078-4088.
  15. Polishchuk PG, et al. QSAR modeling of ocular irritation. SAR QSAR Environ Res. 2021;32(5):371-388.
  16. Yang Y, et al. Robotic-assisted vitrectomy: preliminary report. Retina. 2021;41(4):757-763.
  17. Xu K, et al. Preclinical study of robot-assisted vitrectomy. Transl Vis Sci Technol. 2020;9(2):25.
  18. Miller ST, et al. AI in Ophthalmology: Innovations Shaping 2026. Int J Ophthalmol. 2026;19(1):15-22.
  19. Nankivil D, et al. Toward robot-assisted ophthalmic surgery. Int J Med Robot. 2020;16(5):e2134.
  20. Larsen LB, et al. Robotic surgery: current status. Acta Ophthalmol. 2023;101(4):367-375.
  21. Sahu M, et al. Da Vinci System adaptations. J Robot Surg. 2024;18(2):456.
  22. Chen BK, et al. Minimizing surgical errors with AI. Ophthalmic Res. 2025;68(1):45-52.
  23. Jalamangala S, et al. Deep learning for glaucoma outcomes. Front Artif Intell. 2025;8:1636410.
  24. Harrison G, et al. The rise of AI-assisted surgery. Cureus. 2025;17(2):e12181.
  25. Wang M, et al. Integrating Robotics, AI, and VR. Front Med. 2026;13:8854.
  26. Hatch MR, et al. AI-driven virtual simulators. J Cataract Refract Surg. 2022;48(5):567-574.
  27. Johnson KA, et al. Precision Medicine and AI. J Pers Med. 2021;11(2):78.
  28. Tan GSW, et al. Precision medicines for ocular disorders. Front Med. 2022;9:854215.
  29. Zhang X, et al. AI-Driven Personalized Care. Lancet Digit Health. 2024;6(4):e210-222.
  30. Brown D, et al. Real-world Data for Personalized Care. Ophthalmology. 2023;130(10):1015-1025.
  31. Ting DSW, et al. Personalized anti-VEGF therapy. Ophthalmology. 2021;128(8):1112-1120.
  32. Medeiros FA, et al. AI in stratification for glaucoma. Am J Ophthalmol. 2023;250:89-97.
  33. Kim J, et al. AI-Driven Wearable Bioelectronics. Adv Funct Mater. 2025;35(7):2410410.
  34. Chiang MF, et al. Ophthalmology savvy with IoMT. JAMA Ophthalmol. 2024;142(3):201-210.
  35. Lee S, et al. AI-Based Wearable Sensing. Biosensors. 2025;15(11):756.
  36. Liu Y, et al. AI for treatment response. Lancet Digit Health. 2020;2(10):e527-e536.
  37. Ranasinghe J, et al. Wearables in glaucoma. Transl Vis Sci Technol. 2023;12(7):18.
  38. Morley MG, et al. Ethical considerations of AI. Ophthalmology. 2023;130(5):456-462.
  39. Rajpurkar P, et al. AI in medicine. Nat Med. 2022;28(1):31-38.
  40. Meskó B, et al. Medical professionals in the era of AI. NPJ Digit Med. 2020;3:126.
  41. Topol EJ. Precision medicine. Nat Med. 2024;30(1):49-59.