Clinical utility of an AI-based retinal imaging model for cardiovascular risk prediction in hypertensive retinopathy.

Dongjin Nam¹, Yong-Hwan Jang¹, Yongseok Lee¹, Jaewon Seo², Sahil Thakur³, Simon Nusinovici⁴, Moonsu Kim⁵, Yong Un Shin⁵, Hwan-Cheol Park⁶, Sunjin Hwang⁷

¹Mediwhale Inc., Seoul, South Korea; Department of Internal Medicine, Graduate School, Yonsei University College of Medicine, Seoul, South Korea.

²Mediwhale Inc., Seoul, South Korea.

³Mediwhale Inc., Seoul, South Korea; Singapore Eye Research Institute/Singapore National Eye Center, Singapore.

⁴Mediwhale Inc., Seoul, South Korea; Ophthalmology and Visual Sciences Academic Clinical Program, Duke-NUS Medical School, Singapore.

⁵Noon eye clinic, Guri city, South Korea.

⁶Division of Cardiology, Department of Internal Medicine, Hanyang University Guri Hospital, Guri City, South Korea.

⁷Department of Ophthalmology, Hanyang University College of Medicine, Seoul, South Korea; Department of Ophthalmology, Hanyang University Guri Hospital, Guri city, South Korea. Electronic address: sunjin1989@hanyang.ac.kr.

PubMed DOI

Abstract

OBJECTIVE: This study presents an independent clinical evaluation of Dr.Noon CVD, a commercially developed artificial intelligence (AI)-based retinal imaging model that estimates cardiovascular disease (CVD) risk. We assessed whether the model can effectively evaluate CVD risk in patients with hypertensive retinopathy (HR), a population in which the applicability of conventional CVD risk models re…

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