Biomarkers for Progression in Diabetic Retinopathy: Expanding Personalized Medicine through Integration of AI with Electronic Health Records

Semin Ophthalmol. 2021 May 19;36(4):250-257. doi: 10.1080/08820538.2021.1893351. Epub 2021 Mar 18.

Abstract

The goal of personalized diabetes eye care is to accurately predict in real-time the risk of diabetic retinopathy (DR) progression and visual loss. The use of electronic health records (EHR) provides a platform for artificial intelligence (AI) algorithms that predict DR progression to be incorporated into clinical decision-making. By implementing an algorithm on data points from each patient, their risk for retinopathy progression and visual loss can be modeled, allowing them to receive timely treatment. Data can guide algorithms to create models for disease and treatment that may pave the way for more personalized care. Currently, there exist numerous challenges that need to be addressed before reliably building and deploying AI algorithms, including issues with data quality, privacy, intellectual property, and informed consent.

Keywords: Artificial intelligence; biomarkers; diabetic retinopathy; electronic health records; personalized medicine.

MeSH terms

  • Artificial Intelligence
  • Biomarkers
  • Diabetes Mellitus*
  • Diabetic Retinopathy* / diagnosis
  • Electronic Health Records
  • Humans
  • Precision Medicine

Substances

  • Biomarkers