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Journal article

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

Abstract:

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 show that deep-learning models can be used to identify chronic kidney disease and type 2 diabetes solely from fundus images or in combination with clinical metadata (age, sex, height, weight, body-mass index and blood pressure) with areas under the receiver operating characteristic curve of 0.85–0.93. The models ...

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Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1038/s41551-021-00745-6

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Role:
Author
ORCID:
0000-0002-4549-1697
Publisher:
Springer Nature
Journal:
Nature Biomedical Engineering More from this journal
Volume:
5
Pages:
533-545
Publication date:
2021-06-15
Acceptance date:
2021-05-12
DOI:
EISSN:
2157-846X
Language:
English
Keywords:
Pubs id:
1182249
Local pid:
pubs:1182249
Deposit date:
2021-06-16

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