Rudnicka, Alicja Regina, Welikala, Roshan, Barman, Sarah, Foster, Paul J, Luben, Robert, Hayat, Shabina, Khaw, Kay-Tee, Whincup, Peter, Strachan, David and Owen, Christopher G (2022) Artificial intelligence-enabled retinal vasculometry for prediction of circulatory mortality, myocardial infarction and stroke. British Journal of Ophthalmology, 106, pp. 1722-1729. ISSN (print) 0007-1161

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Official URL:	https://doi.org/10.1136/bjo-2022-321842
Item Type:	Article
Additional Information:	This work was supported by the Medical Research Council Population and Systems Medicine Board (MR/L02005X/1), British Heart Foundation (PG/15/101/31889), Richard Desmond Charitable Trust (via Fight for Sight, Department for Health through the award made by the National Institute for Health Research to Moorfields Eye Hospital and the UCL Institute of Ophthalmology for a Biomedical Research Centre, Medical Research Council, UK (Ref: MR/N003284/1), Cancer Research UK (CRUK, Ref: C864/A8257), and Research into Aging, now known as Age UK (Grant Ref: 262).
Research Area:	Research Areas > Cardiovascular medicine Research Areas > Computer science and informatics
Faculty, School or Research Centre:	Faculty of Science, Engineering and Computing Faculty of Science, Engineering and Computing > School of Computer Science and Mathematics
Date Deposited:	07 Dec 2022 09:44
Last Modified:	15 Oct 2024 15:08
DOI:	https://doi.org/10.1136/bjo-2022-321842
URI:	https://eprints.kingston.ac.uk/id/eprint/52854

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