Ontology highlight
ABSTRACT: Purpose
Prior artificial intelligence (AI) models for predicting glaucoma progression have used traditional classifiers that do not consider the longitudinal nature of patients' follow-up. In this study, we developed survival-based AI models for predicting glaucoma patients' progression to surgery, comparing performance of regression-, tree-, and deep learning-based approaches.Design
Retrospective observational study.Subjects
Patients with glaucoma seen at a single academic center from 2008 to 2020 identified from electronic health records (EHRs).Methods
From the EHRs, we identified 361 baseline features, including demographics, eye examinations, diagnoses, and medications. We trained AI survival models to predict patients' progression to glaucoma surgery us
SUBMITTER: Tao S
PROVIDER: S-EPMC10320266 | biostudies-literature | 2023 Dec
REPOSITORIES: biostudies-literature