Application of a time-series deep learning model to predict cardiac dysrhythmias in electronic health records.

ABSTRACT:

Background

Cardiac dysrhythmias (CD) affect millions of Americans in the United States (US), and are associated with considerable morbidity and mortality. New strategies to combat this growing problem are urgently needed.

Objectives

Predicting CD using electronic health record (EHR) data would allow for earlier diagnosis and treatment of the condition, thus improving overall cardiovascular outcomes. The Guideline Advantage (TGA) is an American Heart Association ambulatory quality clinical data registry of EHR data representing 70 clinics distributed throughout the US, and has been used to monitor outpatient prevention and disease management outcome measures across populations and for longitudinal research on the impact of preventative care.

Methods

For this study, we

SUBMITTER: Guo A 

PROVIDER: S-EPMC8437288 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature