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

Nat Biomed Eng. 2021 Jun;5(6):533-545. doi: 10.1038/s41551-021-00745-6. Epub 2021 Jun 15.


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 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 m2 and 0.65-1.1 mmol l-1, and to stratify patients according to disease-progression risk. We evaluated the generalizability of the models for the identification of chronic kidney disease and type 2 diabetes with population-based external validation cohorts and via a prospective study with fundus images captured with smartphones, and assessed the feasibility of predicting disease progression in a longitudinal cohort.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Area Under Curve
  • Blood Glucose / metabolism
  • Body Height
  • Body Mass Index
  • Body Weight
  • Deep Learning*
  • Diabetes Mellitus, Type 2 / diagnostic imaging*
  • Diabetes Mellitus, Type 2 / metabolism
  • Diabetes Mellitus, Type 2 / pathology
  • Disease Progression
  • Female
  • Fundus Oculi
  • Glomerular Filtration Rate
  • Humans
  • Image Interpretation, Computer-Assisted / statistics & numerical data*
  • Male
  • Metadata / statistics & numerical data
  • Middle Aged
  • Neural Networks, Computer
  • Photography / methods
  • Photography / statistics & numerical data*
  • Prospective Studies
  • ROC Curve
  • Renal Insufficiency, Chronic / diagnostic imaging*
  • Renal Insufficiency, Chronic / metabolism
  • Renal Insufficiency, Chronic / pathology
  • Retina / diagnostic imaging*
  • Retina / metabolism
  • Retina / pathology


  • Blood Glucose