AI-READI: A Multimodal Data Set for Diabetic Eye Research

An NIH-funded project is redefining how artificial intelligence can support ophthalmic research in type 2 diabetes.

By: Aaron Y. Lee, MD, MSCI, Nayoon Gim, BS

Retinal Physician June 1, 2025 Vol 22, Issue June 2025 Page(s): 16-18

Clinical Report: AI-READI: A Multimodal Data Set for Diabetic Eye Research

Overview

The AI-READI project aims to create a comprehensive multimodal dataset for type 2 diabetes research, enhancing the role of artificial intelligence in ophthalmology. By standardizing data across various modalities, the project seeks to improve insights into diabetes management and its ocular complications.

Background

Diabetic eye diseases, particularly diabetic retinopathy, are significant causes of vision loss among individuals with diabetes. Early detection and comprehensive management are crucial to prevent progression. The integration of artificial intelligence in ophthalmic research offers promising avenues for improving diagnostic accuracy and patient outcomes.

Data Highlights

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Key Findings

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Clinical Implications

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Conclusion

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