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

Abstract

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 AIbased “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.

Lead Participant

Project Cost

Grant Offer

QUEEN'S UNIVERSITY OF BELFAST £323,759 £ 323,759
 

Participant

INNOVATE UK

Publications

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