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Related Experiment Video

Updated: Jul 13, 2026

Using Retinal Imaging to Study Dementia
09:17

Using Retinal Imaging to Study Dementia

Published on: November 6, 2017

Deep Learning-Derived Retinal Age Detects Cognitive Impairment.

Minkyu Kim1, Kenneth Um2, Gui-Shuang Ying1,3

  • 1Department of Ophthalmology, Scheie Eye Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania.

Ophthalmology Science
|July 12, 2026
PubMed
Summary

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Diabetic Retinopathy01:27

Diabetic Retinopathy

DefinitionDiabetic retinopathy is a microvascular complication of diabetes affecting the retinal blood vessels.Risk FactorsDiabetic retinopathy is present in almost all individuals with type 1 diabetes and more than 60% of those with type 2 diabetes after two decades of disease.The risk increases with poor glycemic control, hypertension, dyslipidemia, smoking, pregnancy, and puberty.Although cataracts and glaucoma are also more frequent in people with diabetes, retinopathy remains the leading...

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Deep learning-based retinal age is a better predictor of cognitive decline than chronological age. This eye-scan biomarker shows promise for early detection of cognitive impairment in clinical settings.

Area of Science:

  • Ophthalmology
  • Neurology
  • Artificial Intelligence

Background:

  • Cognitive impairment poses a significant public health challenge.
  • Early detection of cognitive decline is crucial for timely intervention.
  • Biomarkers that can predict cognitive function are needed.

Purpose of the Study:

  • To investigate the association between deep learning-derived retinal age and cognitive function.
  • To evaluate if retinal age is a superior screening tool for cognitive impairment compared to chronological age.

Main Methods:

  • A cross-sectional analysis of 1049 participants from the AI-READI cohort was performed.
  • Retinal age was estimated using a deep learning model on fundus photographs.
  • Cognitive function was assessed using the Montreal Cognitive Assessment (MoCA), with impairment defined as MoCA score <26.
Keywords:
Biomarker.Cognitive impairmentDeep learningFundus photographyRetinal age

Related Experiment Videos

Last Updated: Jul 13, 2026

Using Retinal Imaging to Study Dementia
09:17

Using Retinal Imaging to Study Dementia

Published on: November 6, 2017

Main Results:

  • Retinal age showed a stronger correlation with MoCA scores than chronological age (R=-0.47 vs. -0.21).
  • Retinal age was significantly associated with cognitive impairment in a dose-response manner (adjusted RR for highest quartile: 10.13).
  • Retinal age demonstrated higher accuracy in detecting cognitive impairment than chronological age (AUC 0.83 vs. 0.66 with covariates).

Conclusions:

  • Deep learning-derived retinal age is a potent biological biomarker for cognitive function.
  • Retinal age outperforms chronological age in predicting cognitive impairment.
  • This scalable, image-based biomarker offers potential for opportunistic screening and early detection of cognitive decline.