Deep-learning models for the detection and incidence prediction of chronic kidney disease and type 2 diabetes from retinal fundus images

K Zhang, X Liu, J Xu, J Yuan, W Cai, T Chen… - Nature biomedical …, 2021 - nature.com
Regular screening for the early detection of common chronic diseases might benefit from the
use of deep-learning approaches, particularly in resource-poor or remote settings. Here we …

Deep-learning models for the detection and incidence prediction of chronic kidney disease and type 2 diabetes from retinal fundus images.

K Zhang, X Liu, J Xu, J Yuan, W Cai… - Nature Biomedical …, 2021 - europepmc.org
Regular screening for the early detection of common chronic diseases might benefit from the
use of deep-learning approaches, particularly in resource-poor or remote settings. Here we …

Deep-learning models for the detection and incidence prediction of chronic kidney disease and type 2 diabetes from retinal fundus images

K Zhang, X Liu, J Xu, J Yuan, C Wenjia… - Nature Biomedical …, 2021 - search.proquest.com
Regular screening for the early detection of common chronic diseases might benefit from the
use of deep-learning approaches, particularly in resource-poor or remote settings. Here we …

Deep-learning models for the detection and incidence prediction of chronic kidney disease and type 2 diabetes from retinal fundus images

K Zhang, X Liu, J Xu, J Yuan, W Cai… - Nature biomedical …, 2021 - pubmed.ncbi.nlm.nih.gov
Regular screening for the early detection of common chronic diseases might benefit from the
use of deep-learning approaches, particularly in resource-poor or remote settings. Here we …

Deep-learning models for the detection and incidence prediction of chronic kidney disease and type 2 diabetes from retinal fundus images

K Zhang, X Liu, J Xu, J Yuan, W Cai, T Chen… - Nature Biomedical …, 2021 - ora.ox.ac.uk
Regular screening for the early detection of common chronic diseases might benefit from the
use of deep-learning approaches, particularly in resource-poor or remote settings. Here we …