Digital Care Team for AD Risk Assessment: Integrating Retinal Biomarkers, RWD, and AI-Driven Analysis for Early Detection

This project proposes an innovative AI-driven screening tool that combines retinal imaging biomarkers with real-world data to enable early AD risk assessment. The tool can automatically extract retinal information from non-invasive imaging techniques, such as Optical Coherence Tomography, and integrate it with patient history from electronic health records to create a personalized risk profile. Additionally, this tool is supported by a digital care team composed of AI agents specializing in ophthalmology, neurology, and other related fields. These AI agents collaborate to assess risk factors and generate personalized AD risk reports, assisting clinicians in early diagnosis and intervention.

In this project, we will conduct a large-scale study utilizing patient data from IU Health and Yale University. If successful, this tool could enhance AD risk screening by making it more accessible and cost-effective. Future developments will focus on integrating it into clinical workflows. By enabling early detection, this project has the potential to improve patient outcomes and reduce the burden of AD on individuals and healthcare systems.