This paper is in the following e-collection/theme issue:

Applications of AI (130) Artificial Intelligence (1556)

Published on in Vol 3 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/48295, first published .
Machine Learning Methods Using Artificial Intelligence Deployed on Electronic Health Record Data for Identification and Referral of At-Risk Patients From Primary Care Physicians to Eye Care Specialists: Retrospective, Case-Controlled Study

Machine Learning Methods Using Artificial Intelligence Deployed on Electronic Health Record Data for Identification and Referral of At-Risk Patients From Primary Care Physicians to Eye Care Specialists: Retrospective, Case-Controlled Study

Machine Learning Methods Using Artificial Intelligence Deployed on Electronic Health Record Data for Identification and Referral of At-Risk Patients From Primary Care Physicians to Eye Care Specialists: Retrospective, Case-Controlled Study

Authors of this article:

Joshua A Young1 Author Orcid Image ;   Chin-Wen Chang2 Author Orcid Image ;   Charles W Scales3 Author Orcid Image ;   Saurabh V Menon4 Author Orcid Image ;   Chantal E Holy5 Author Orcid Image ;   Caroline Adrienne Blackie6 Author Orcid Image
Article Authors Cited by (3) Tweetations (2) Metrics

Journals

  1. Yılmaz İ. The Rise of the Machines: Artificial Intelligence in Ophthalmology - A Boon or Bane?. Experimental and Applied Medical Science 2024;5(2):61 View
  2. Mohammad N, Rajab I, Al-Taie R, Ismail M. Machine Learning and Vision: Advancing the Frontiers of Diabetic Cataract Management. Cureus 2024 View
  3. Ayers A, Ho C, Kerr D, Cichosz S, Mathioudakis N, Wang M, Najafi B, Moon S, Pandey A, Klonoff D. Artificial Intelligence to Diagnose Complications of Diabetes. Journal of Diabetes Science and Technology 2025;19(1):246 View