Deep-learning models for the detection and incidence prediction of chronic kidney disease and type 2 diabetes from retinal fundus images.
Zhang K, Liu X, Xu J, Yuan J, Cai W, Chen T, Wang K, Gao Y, Nie S, Xu X, Qin X, Su Y, Xu W, Olvera A, Xue K, Li Z, Zhang M, Zeng X, Zhang CL, Li O, Zhang EE, Zhu J, Xu Y, Kermany D, Zhou K, Pan Y, Li S, Lai IF, Chi Y, Wang C, Pei M, Zang G, Zhang Q, Lau J, Lam D, Zou X, Wumaier A, Wang J, Shen Y, Hou FF, Zhang P, Xu T, Zhou Y, Wang G.
Zhang K, et al.
Nat Biomed Eng. 2021 Jun;5(6):533-545. doi: 10.1038/s41551-021-00745-6. Epub 2021 Jun 15.
Nat Biomed Eng. 2021.
PMID: 34131321
The models were trained and validated with a total of 115,344 retinal fundus photographs from 57,672 patients and can also be used to predict estimated glomerulal filtration rates and blood-glucose levels, with mean absolute errors of 11.1-13.4 ml min(-1) per 1.73 m(2) and 0.65-1 …
The models were trained and validated with a total of 115,344 retinal fundus photographs from 57,672 patients and can also be used to predic …