Generative Artificial Intelligence in Ophthalmology
eBook - ePub

Generative Artificial Intelligence in Ophthalmology

  1. 832 pages
  2. English
  3. ePUB (mobile friendly)
  4. Available on iOS & Android
eBook - ePub

About this book

Empower your clinical practice to lead the future of vision science with this guide to mastering generative AI strategies that transform complex imaging data into high-precision, ethical diagnostic solutions.

Generative AI is a game-changer for both artificial intelligence and healthcare, especially in the field of vision science. As ophthalmologists and other eye care professionals work toward increasing the accuracy of diagnoses and treatment outcomes to improve patient-centered service delivery, generative AI is showing emerging potential as a tool to accomplish these goals. Generative AI, particularly generative adversarial networks, shows potential as a solution for image enhancement, data management, and personalized patient care.

This cross-disciplinary work addresses not only the technical challenges in building effective AI systems but also the ethical considerations of using these technologies in clinical scenarios. The book bridges the knowledge gap between AI researchers and healthcare professionals by breaking down complex AI concepts into clear, accessible language, providing practical examples of real-world applications, and guiding readers through the ethical and regulatory challenges of integrating AI into clinical practice. It demonstrates how advanced AI can be applied effectively in ophthalmology to improve diagnostics, treatment planning, and—accessibility.

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Information

Year
2026
Print ISBN
9781394358175
eBook ISBN
9781394358182

Table of contents

  1. Cover
  2. Table of Contents
  3. Series Page
  4. Title Page
  5. Copyright Page
  6. Brief Contents of Volume 2
  7. Preface
  8. Series Page
  9. Title Page
  10. Copyright Page
  11. Brief Contents of Volume 1
  12. Preface
  13. 1 Applying Ethical AI to Synthetic Image Generation in Ophthalmology
  14. 2 Generative AI for Low-Resource Vision Care: Creating Synthetic Images
  15. 3 Cross-Modality Image Synthesis in Vision Care Using Generative AI
  16. 4 Synthetic Imaging for Enhanced Vision Diagnostics
  17. 5 Generative AI for Low-Resource Settings: Enhancing Ophthalmic Diagnostics
  18. 6 Ethical AI in Ophthalmology: Improving Model Accuracy with GANs
  19. 7 Ethical and Regulatory Considerations in AI-Driven Ophthalmology
  20. 8 Ethics and Regulations in Generative AI for Vision Diagnostics
  21. 9 Generative AI in Ophthalmology: Precision in Treatment Prediction
  22. 10 Generative AI in Ophthalmology: Overcoming GAN Implementation Challenges
  23. 11 Generative AI for Low-Resource Vision Care: Enabling Patient-Specific Modeling
  24. 12 Advancing Ophthalmic Diagnostics with Generative AI
  25. 13 Leveraging Generative AI for Assistive Technologies in Vision Care
  26. 14 AI in Low-Resource Settings: Enhancing Ophthalmic Models with Synthetic Data
  27. 15 Boosting Ophthalmic Model Accuracy with Generative AI and Synthetic Imaging
  28. 16 Overcoming GAN Challenges to Improve Ophthalmic Model Accuracy
  29. 17 Patient-Specific Ophthalmic Modeling with Generative AI
  30. 18 Synthetic Image Generation for Patient-Specific Ophthalmic Models: A Comprehensive Review
  31. 19 Cross-Modality Image Synthesis for Personalized Vision Treatment
  32. 20 Personalized Medicine in Vision Care through AI-Driven Image Synthesis
  33. 21 Predicting Treatment Outcomes in Ophthalmology with Generative AI
  34. 22 Predicting Vision Care Outcomes with Personalized Generative AI
  35. 23 Shaping Ophthalmic Imaging: The Challenges of Implementing GANs
  36. 24 Challenges in Using GANs for Synthetic Imaging in Vision Diagnostics
  37. 25 Generative AI for Assistive Vision Technologies: A New Era in Care
  38. 26 A New Era in Vision Care: Overview of AI Transforming the World of Ophthalmology
  39. 27 Creating Synthetic Images for Improved Diagnostics
  40. 28 Enhancing the Accuracy of Ophthalmic Models
  41. 29 Predicting Treatment Outcomes with Generative Adversarial Networks
  42. 30 GAN-Driven Approaches for Cross-Modality Image Synthesis
  43. 31 AI for Low-Resource Settings and Assistive Technologies: Utilization of GANs for the Generation of Synthetic Data in Resource-Constrained Contexts When Acquiring Extensive Datasets Poses a Barrier
  44. 32 AI-Enabled Personalized Medicine and Patient-Specific Monitoring
  45. 33 The Challenges of Implementing GANs
  46. 34 Ethics and Regulations in AI-Driven Ophthalmology
  47. 35 AI in Preventive Eye Care
  48. 36 Collaborative AI in Smart Eye Care: Integration of AI, IoT, and Wearable Technologies for Eye Health Monitoring
  49. 37 Exploring Adaptive Multimodal Generative AI for Personalized Content Creation
  50. 38 Self-Supervised Learning for Early Detection of Diabetic Retinopathy: A Generative AI Perspective
  51. 39 Future Directions: From Generative AI to General AI in Ophthalmic Care
  52. Index
  53. Also of Interest
  54. End User License Agreement

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Yes, you can access Generative Artificial Intelligence in Ophthalmology by Binod Kumar Mishra,Abhishek Kumar,K. Mariyappan,Vibha Tiwari,Pramod Singh Rathore,Gaur Hari Das in PDF and/or ePUB format, as well as other popular books in Medicine & Artificial Intelligence (AI) & Semantics. We have over 1.5 million books available in our catalogue for you to explore.