Multimodal Artificial Intelligence Models Predicting Glaucoma Progression Using Electronic Health Records and Retinal Nerve Fiber Layer Scans.

Journal: Translational vision science & technology
PMID: 40152766

Abstract

PURPOSE: The purpose of this study was to develop models that predict which patients with glaucoma will progress to require surgery, combining structured data from electronic health records (EHRs) and retinal fiber layer optical coherence tomography (RNFL OCT) scans.

Authors

  • Abigail Koornwinder
    Department of Ophthalmology, Byers Eye Institute, Stanford University, Palo Alto, CA, USA.
  • Youchen Zhang
    Department of Ophthalmology, Byers Eye Institute, Stanford University, Palo Alto, CA, USA.
  • Rohith Ravindranath
    Department of Ophthalmology, Byers Eye Institute, Stanford University, Palo Alto, California.
  • Robert T Chang
    Department of Ophthalmology, Byers Eye Institute, Stanford University, Palo Alto, California.
  • Isaac A Bernstein
    Department of Ophthalmology, Byers Eye Institute, Stanford University, Stanford, California.
  • Sophia Y Wang
    School of Medicine, Stanford University, Palo Alto, CA, United States.

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