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DETECT AND PROFILE AGE-RELATED MACULAR DEGENERATION

A real-world AI-based infrastructure for screening and prediction of progression in age-related macular degeneration (AMD) providing accessible shared care

Impact

Economic and Social Impact on Eye Care: Addressing resource constraints in eye care, the project counters an overburdened system exacerbated by a growing ageing population at risk of AMD. By enabling opticians, optometrists, and other eye care professionals to contribute to primary care through AI-based disease detection, the project supports a shift in care-sharing. The economic impact is substantial, with the total cost of managing severe/late-stage AMD in the EU expected to be €89.46 billion per year. AI's cost-effectiveness, compared to manual screening, extends to the delivery of digital datasets for predictive healthcare budgeting and outcomes optimization.

AI-Based Precision Medicine and Shared Care: The I-SCREEN platform introduces AI-based decision support systems, bringing precision medicine to ocular and systemic disease management. Eliminating subjective variability, reducing time-to-treatment, saving time for both physicians and patients, and establishing equal quality standards enhance the socio-economic impact. Citizens benefit from increased accessibility to rapid diagnosis, personalised risk prediction, and timely treatment. The system significantly reduces the disease burden, enabling early asymptomatic disease diagnosis with optimal cure perspectives.

Advancement in AI Technology: The project serves as a proof of concept for trustworthy AI systems in disease detection and risk estimation using OCT imaging. This scientific and technological advance contributes to the broader field of AI in healthcare, providing guidance for similar systems in various medical imaging-oriented specialties. The impact is evident in reported sensitivity and specificity of AI systems, influencing the adoption rate among healthcare professionals.

Reduction of Disease Burden for Healthy Aging: With a direct contribution to UN Sustainable Development Goals, particularly SDG 3 and SDG 17, the project addresses the increased burden of blindness and vision impairment in an ageing population. The AI screening system promotes healthy ageing, reduces inequalities related to ageing, and leverages existing care infrastructure. Shared care reduces costs, with a tangible impact measured by a decrease in Disability-Adjusted Life Years (DALY) due to vision loss.

Health Policies and Resilient Access: Optimised healthcare measures and a more resilient health care access system result from the project's new shared care approach. Community-based eye care providers become integral to early detection of various chronic non-communicable diseases in their early stages, enhancing overall health policies.