Objective:

To explore the use of artificial intelligence (AI) in reducing undertreatment and overtreatment of neovascular age-related macular degeneration (nAMD), highlighting the significance of these issues in patient care.

Key Findings:

• AI can effectively reduce both undertreatment and overtreatment of nAMD.
• Training AI on multiple imaging devices enhances its performance and reliability.
• Collaboration between AI and clinicians improves diagnostic accuracy and management plans.
• Patient trust is essential for the acceptance of AI in treatment decisions.
• Ethical considerations must be integrated into AI development and deployment.

Interpretation:

The integration of AI in ophthalmology shows promise in enhancing patient care, but requires careful consideration of ethical, legal, and practical implications, with ongoing research needed.

Limitations:

• The study's findings may not be generalizable to all imaging devices beyond those tested.
• Liability and regulatory frameworks for AI in healthcare remain uncertain.
• Potential biases in AI training data could affect outcomes.

Conclusion:

AI has the potential to transform nAMD treatment by improving diagnostic accuracy and patient outcomes, provided that ethical considerations, patient trust, and collaboration between AI and clinicians are prioritized.