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

Authors
  • Channa, Roomasa1, 2, 3
  • Wolf, Risa4
  • Abramoff, Michael D5, 6, 7
  • 1 Department of Ophthalmology, Baylor College of Medicine, Houston, TX, USA.
  • 2 Michael DeBakey Veterans Affairs Hospital, Houston, TX, USA.
  • 3 Wilmer Eye Institute, Johns Hopkins University, Baltimore, MD, USA.
  • 4 Pediatric Endocrinology, Johns Hopkins University, Baltimore, MD, USA.
  • 5 The Robert C. Watzke Professor of Ophthalmology and Visual Sciences, University of Iowa, Iowa City, IA, USA.
  • 6 VA Medical Center, Iowa City, IA, USA.
  • 7 IDx, Coralville, IA, USA.
Type
Published Article
Journal
Journal of Diabetes Science and Technology
Publisher
SAGE Publications
Publication Date
May 01, 2021
Volume
15
Issue
3
Pages
695–698
Identifiers
DOI: 10.1177/1932296820909900
PMID: 32126819
Source
Medline
Keywords
Language
English
License
Unknown

Abstract

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.

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