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Health-monitoring with AI-enabled smartphone-based imaging of the eye

CORDIS · observation · Publication date unknown

ical and sensory capabilities, taking diagnostic-quality snapshots of the eye fundus is becoming a viable option. This poses a paramount opportunity to turn the smartphone imaging with the support of artificial intelligence (AI) into a powerful health monitoring tool. The proposed research will advance the AI methodology and provide a proof-of-concept in retinal disease monitoring. It is based on the hypothesis that the disease-specific biomarkers visible on gold-standard 3D OCT imaging are recoverable with AI from 2D portable fundus imaging provided by smartphones. In a unique interdisciplinary setting, it aims to (i) build multimodal foundation AI models based on a large amount of available retrospective imaging data, (ii) advance the AI methodology to distill across the imaging modalities the knowledge accrued by the models, and (iii) in a clinical study demonstrate that AI models operating on smartphone-based fundus images are comparable to their high-end optical imaging counterparts across diagnostic tasks. The work will lead to a potentially disruptive, accessible and scalable

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recordType

award

status

SIGNED

region

EU

value

1999809

unit

EUR