Machine Learning-Based Predictive Modeling of Surgical Intervention in Glaucoma Using Systemic Data From Electronic Health Records.

Journal: American journal of ophthalmology
Published Date:

Abstract

PURPOSE: To predict the need for surgical intervention in patients with primary open-angle glaucoma (POAG) using systemic data in electronic health records (EHRs).

Authors

  • Sally L Baxter
    Viterbi Family Department of Ophthalmology, University of California, San Diego, La Jolla.
  • Charles Marks
    UCSD Health Department of Biomedical Informatics, University of California, San Diego, La Jolla, California, USA; Interdisciplinary Research on Substance Use Joint Doctoral Program, University of California, San Diego and San Diego State University, San Diego, California, USA.
  • Tsung-Ting Kuo
    University of California San Diego, La Jolla, CA.
  • Lucila Ohno-Machado
    University of California San Diego, La Jolla, CA.
  • Robert N Weinreb
    Hamilton Glaucoma Center, Viterbi Family Department of Ophthalmology and Shiley Eye Institute, University of California, San Diego, La Jolla, California.