Artificial Intelligence Improves Patient Follow-Up in a Diabetic Retinopathy Screening Program.

Journal: Clinical ophthalmology (Auckland, N.Z.)
Published Date: Nov 2, 2023

Abstract

PURPOSE: We examine the rate of and reasons for follow-up in an Artificial Intelligence (AI)-based workflow for diabetic retinopathy (DR) screening relative to two human-based workflows.

Authors

  • Eliot R Dow
    Department of Ophthalmology, Byers Eye Institute at Stanford, Palo Alto, CA, USA.
  • Karen M Chen
    Department of Ophthalmology, Byers Eye Institute at Stanford, Palo Alto, CA, USA.
  • Cindy S Zhao
    Department of Ophthalmology, Byers Eye Institute at Stanford, Palo Alto, CA, USA.
  • Austen N Knapp
    Department of Ophthalmology, Byers Eye Institute at Stanford, Palo Alto, CA, USA.
  • Anuradha Phadke
    Department of Internal Medicine, Stanford Health Care, Palo Alto, CA, USA.
  • Kirsti Weng
    Department of Internal Medicine, Stanford Health Care, Palo Alto, CA, USA.
  • Diana V Do
    Department of Ophthalmology, Byers Eye Institute at Stanford, Palo Alto, CA, USA.
  • Vinit B Mahajan
    Department of Ophthalmology, Byers Eye Institute at Stanford, Palo Alto, CA, USA.
  • Prithvi Mruthyunjaya
    Department of Ophthalmology, Byers Eye Institute at Stanford, Palo Alto, CA, USA.
  • Theodore Leng
    Department of Ophthalmology, Byers Eye Institute at Stanford, Palo Alto, CA, USA.
  • David Myung
    Department of Ophthalmology, Byers Eye Institute at Stanford, Palo Alto, CA, USA.

Keywords

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