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Updated: Oct 29, 2025

An Acute Retinal Model for Evaluating Blood Retinal Barrier Breach and Potential Drugs for Treatment
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Systemic retinal biomarkers.

Tushar M Ranchod1

  • 1Bay Area Retina Associates, Walnut Creek, California, USA.

Current Opinion in Ophthalmology
|July 7, 2021
PubMed
Summary
This summary is machine-generated.

Systemic retinal biomarkers show promise for diagnosing diseases like cardiovascular and kidney conditions. Advanced techniques, including deep learning, are improving their accuracy and clinical application.

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Area of Science:

  • Ophthalmology
  • Cardiology
  • Nephrology
  • Neurology

Background:

  • Systemic retinal biomarkers are indicators in the retina linked to overall health.
  • Their potential for evaluating and managing systemic diseases is increasingly recognized.

Purpose of the Study:

  • To review the background, categories, and key findings of systemic retinal biomarker research.
  • To explore potential applications of these biomarkers in clinical practice.

Main Methods:

  • Identification of biomarkers using regression analysis and advanced image processing.
  • Application of deep learning techniques for disease prediction.
  • Development of virtual coronary artery calcium scoring models.

Main Results:

  • Systemic retinal biomarkers show potential for cardiovascular, kidney, and neurodegenerative diseases.
  • Deep learning models accurately predict conditions such as anemia and chronic kidney disease.
  • Virtual coronary artery calcium scoring demonstrates competitive predictive performance.

Conclusions:

  • Research in systemic retinal biomarkers has advanced significantly through regression studies and deep learning.
  • Future research can enhance biomarker performance with larger datasets, metadata, and higher-resolution imaging.