Cardiovascular disease risk assessment using a deep-learning-based retinal biomarker: a comparison with existing risk scores

Autor: Joseph Keunhong Yi, Tyler Hyungtaek Rim, Sungha Park, Sung Soo Kim, Hyeon Chang Kim, Chan Joo Lee, Hyeonmin Kim, Geunyoung Lee, James Soo Ghim Lim, Yong Yu Tan, Marco Yu, Yih-Chung Tham, Ameet Bakhai, Eduard Shantsila, Paul Leeson, Gregory Y H Lip, Calvin W L Chin, Ching-Yu Cheng

Publikováno v: Yi, J K, Rim, T H, Park, S, Kim, S S, Kim, H C, Lee, C J, Kim, H, Lee, G, Lim, J S G, Tan, Y Y, Yu, M, Tham, Y-C, Bakhai, A, Shantsila, E, Leeson, P, Lip, G Y H, Chin, C W L & Cheng, C-Y 2023, ' Cardiovascular disease risk assessment using a deep-learning-based retinal biomarker : a comparison with existing risk scores ', European Heart Journal-Digital Health, vol. 4, no. 3, pp. 236-244 . https://doi.org/10.1093/ehjdh/ztad023

Aims This study aims to evaluate the ability of a deep-learning-based cardiovascular disease (CVD) retinal biomarker, Reti-CVD, to identify individuals with intermediate- and high-risk for CVD. Methods and results We defined the intermediate- and hig

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::84b4ccc086c73bd679c410347efada37
https://doi.org/10.1093/ehjdh/ztad023

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