Autonomous Artificial Intelligence in Diabetic Retinopathy: From Algorithm to Clinical Application

Roomasa Channa, Risa Wolf, Michael D. Abramoff

Research output: Contribution to journalComment/debatepeer-review


Artificial intelligence (AI)-based algorithms are rapidly entering the health care field and have the potential to improve patient care. Our article focuses on the use of autonomous AI algorithms (ie, algorithms that can make clinical decisions without human oversight) in diagnostic imaging. In this article, we have used the example of diabetic retinopathy screening to highlight some important aspects to be considered by developers, policymakers, and end users when bringing autonomous AI algorithms into clinical practice. We have divided these aspects into (1) following the principles of safety, efficacy, and equity in all phases of development and implementation of the algorithm; (2) regulatory processes involving medical records, medical liability, and patient privacy; (3) cost and billing; and (4) the role of health care providers.

Original languageEnglish (US)
Pages (from-to)695-698
Number of pages4
JournalJournal of Diabetes Science and Technology
Issue number3
StatePublished - 2020


  • artificial intelligence
  • augmented intelligence
  • clinical practice
  • implementation
  • regulation

ASJC Scopus subject areas

  • Internal Medicine
  • Endocrinology, Diabetes and Metabolism
  • Bioengineering
  • Biomedical Engineering


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