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

Project description

Combatting age-related macular degeneration with early detection

Age-related macular degeneration (AMD) is a prevalent eye condition, with late-stage AMD being the leading cause of legal blindness in individuals over 50, affecting over 110 million people worldwide. The challenge lies in detecting AMD early, before irreversible vision loss occurs. With this in mind, the EIC-funded I-SCREEN project will develop an AI-based diagnostic system for early AMD detection and monitoring. Bringing together clinical experts, AI developers, and opticians, this multidisciplinary endeavour creates innovative, cloud-based tools for widespread AMD screening. With its focus on data-efficient AI learning and longitudinal OCT data analysis, I-SCREEN promises unprecedented accessibility to vision-saving care, setting a new standard for disease screening and management.

Objective

The aim of I(eye)-Screen is to develop an artificial intelligence (AI)-based diagnostic decision support system for screening and monitoring of age-related macular degeneration (AMD) at an early stage before vision loss occurs. Late AMD is the leading cause of legal blindness >50 years with 110 mio individuals at risk. The multidisciplinary consortium brings together a network of clinical retina experts, computer scientists working at the cutting edge of AI development, an infrastructure of community-based opticians/optometrists and an SME experienced in digital platform performance to develop innovative and trustworthy AI tools for broad, real-time AMD screening and monitoring via a cloud-based infrastructure with unlimited access. To achieve the ambitious goal of finding “the needle in the haystack” in early AMD, Optical Coherence Tomography (OCT), a high-resolution, effortless imaging modality is used providing a detailed characterization of the retina in extensive volumetric scans. Breakthrough AI approaches for medical imaging will be developed to enable data-efficient and robust learning from sparse longitudinal OCT data to systematically analyse dense data volumes and identify (sub)clinical markers of disease activity. Clinical sites throughout Europe will collect a longitudinal cohort serving for calibrating and fine-tuning algorithms using the high-end OCT device available at eye clinics. Innovative AI technology will then be created to transfer the detection and monitoring tools to low-cost devices used in next door opticians’/optometrists’ offices. The timing of the project perfectly fits the recent regulatory approval of the first therapy to halt progression of the major atrophic type of AMD. The resulting AI-based “shared care” strategy offers unrestricted accessibility to vision-maintaining care with greatest health equity and provides a role model for screening for systemic, cardiovascular and neurodegenerative disease reflecting retinal biomarkers.

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HORIZON-EIC - HORIZON EIC Grants

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Call for proposal

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(opens in new window) HORIZON-EIC-2023-PATHFINDEROPEN-01

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Coordinator

MEDIZINISCHE UNIVERSITAET WIEN
Net EU contribution

Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.

€ 1 333 540,00
Address
SPITALGASSE 23
1090 Wien
Austria

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Region
Ostösterreich Wien Wien
Activity type
Higher or Secondary Education Establishments
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Total cost

The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.

€ 1 333 540,00

Participants (7)

Partners (4)

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