Predictive Analytics for Glaucoma Using Data From the All of Us Research Program.

ABSTRACT:

Purpose

To (1) use All of Us (AoU) data to validate a previously published single-center model predicting the need for surgery among individuals with glaucoma, (2) train new models using AoU data, and (3) share insights regarding this novel data source for ophthalmic research.

Design

Development and evaluation of machine learning models.

Methods

Electronic health record data were extracted from AoU for 1,231 adults diagnosed with primary open-angle glaucoma. The single-center model was applied to AoU data for external validation. AoU data were then used to train new models for predicting the need for glaucoma surgery using multivariable logistic regression, artificial neural networks, and random forests. Five-fold cross-validation was performed. Model performance was

SUBMITTER: Baxter SL 

PROVIDER: S-EPMC8184631 | biostudies-literature | 2021 Jul

REPOSITORIES: biostudies-literature