Journal article

A deep-learning system for the assessment of cardiovascular disease risk via the measurement of retinal-vessel calibre

Carol Y Cheung, Dejiang Xu, Ching-Yu Cheng, Charumathi Sabanayagam, Yih-Chung Tham, Marco Yu, Tyler Hyungtaek Rim, Chew Yian Chai, Bamini Gopinath, Paul Mitchell, Richie Poulton, Terrie E Moffitt, Avshalom Caspi, Jason C Yam, Clement C Tham, Jost B Jonas, Ya Xing Wang, Su Jeong Song, Louise M Burrell, Omar Farouque Show all

Nature Biomedical Engineering | NATURE RESEARCH | Published : 2020

Abstract

Retinal blood vessels provide information on the risk of cardiovascular disease (CVD). Here, we report the development and validation of deep-learning models for the automated measurement of retinal-vessel calibre in retinal photographs, using diverse multiethnic multicountry datasets that comprise more than 70,000 images. Retinal-vessel calibre measured by the models and by expert human graders showed high agreement, with overall intraclass correlation coefficients of between 0.82 and 0.95. The models performed comparably to or better than expert graders in associations between measurements of retinal-vessel calibre and CVD risk factors, including blood pressure, body-mass index, total chol..

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Grants

Awarded by Singapore Ministry of Health's National Medical Research Council (NMRC)


Awarded by National Research Foundation, Singapore, under its AI Singapore Programme (AISG Award)


Funding Acknowledgements

We thank all of the staff at the SNEC Ocular Reading Centre (SORC) for their contribution to this study. We acknowledge funding support from Singapore Ministry of Health's National Medical Research Council (NMRC) grants OFLCG/001/2017, NMRC/STaR/003/2008, NMRC/STaR/0016/2013 and NMRC/CIRG/1371/2013. This research is also supported by the National Research Foundation, Singapore, under its AI Singapore Programme (AISG Award no. AISG-GC-2019-001). Any opinions, findings and conclusions or recommendations expressed in this material are those of the authors and do not reflect the views of the National Research Foundation, Singapore.