AI & Retina Innovations Dinner Summary

‍Purpose of the Evening

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The dinner was designed to:

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• Explore practical applications of AI in retinal disease detection and management
• Share emerging clinical insights in AMD and diabetic macular edema (DME)
• Discuss how biomarkers are shaping earlier diagnosis and treatment decisions
• Foster peer discussion on integrating telemedicine into optometric practice

Key Clinical Themes

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1. AI in Retinal Imaging and Screening

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Discussion focused on how AI tools are increasingly used to support early detection and triage of retinal disease. Key points included:

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• Improved efficiency in identifying high-risk patients
• Enhanced support for clinical decision-making
• Potential to reduce diagnostic delays in routine screening workflows

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2. Biomarkers in AMD and DME

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The session highlighted evolving evidence around imaging and fluid-based biomarkers. Key takeaways included:

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• Biomarkers as predictors of disease progression
• Their role in guiding treatment timing and intensity
• Growing clinical utility in personalizing patient management

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3. Telemedicine and Collaborative Care Models

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Participants explored how tele-ophthalmology is expanding access to retina care. Highlights included:

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• Improved collaboration between optometry and ophthalmology
• Increased access for patients in underserved regions
• Integration opportunities within existing clinical workflows

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Key Takeaways

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• AI is becoming an important adjunct tool in retinal disease detection and management
• Biomarkers are increasingly central to understanding AMD and DME progression
• Telemedicine is enabling more collaborative and accessible retina care models
• Strong interest exists in practical implementation within optometric practice

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Notable Insights

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• “AI is not replacing clinical judgment, but enhancing it through earlier and more consistent detection support.”
• “Biomarkers are shifting retina care toward more predictive and individualized treatment strategies.”

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