Automated and Computer-Assisted Detection, Classification, and Diagnosis of Diabetic Retinopathy

Michael D. Abramoff, Theodore Leng, Daniel S.W. Ting, Kyu Rhee, Mark B. Horton, Christopher J Brady, and Michael F. Chiang

Systems for computer-assisted and fully automated detection, triage, and diagnosis of diabetic retinopathy (DR) from retinal images show great variation in design, level of autonomy, and intended use. Moreover, the degree to which these systems have been evaluated and validated is heterogeneous. We use the term DR artificial intelligence (AI) system as a general term for any system that interprets retinal images with at least some degree of autonomy from a human grader.

The introduction of AI in medicine has raised significant ethical, economic, and scientific controversies. Because an explicit goal of AI is to perform processes previously reserved for human clinicians and other health care personnel, there is justified concern about the impact on patient safety, efficacy, equity, and liability, and the labor market.