Deep Learning Approaches for Predicting Glaucoma Progression Using Electronic Health Records and Natural Language Processing.

ABSTRACT:

Purpose

Advances in artificial intelligence have produced a few predictive models in glaucoma, including a logistic regression model predicting glaucoma progression to surgery. However, uncertainty exists regarding how to integrate the wealth of information in free-text clinical notes. The purpose of this study was to predict glaucoma progression requiring surgery using deep learning (DL) approaches on data from electronic health records (EHRs), including features from structured clinical data and from natural language processing of clinical free-text notes.

Design

Development of DL predictive model in an observational cohort.

Participants

Adult patients with glaucoma at a single center treated from 2008 through 2020.

Methods

Ophthalmology clinical notes of pat

SUBMITTER: Wang SY 

PROVIDER: S-EPMC9559076 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature