AI Algorithm to Predict Acute Coronary Syndrome in Prehospital Cardiac Care: Retrospective Cohort Study.

ABSTRACT:

Background

Overcrowding of hospitals and emergency departments (EDs) is a growing problem. However, not all ED consultations are necessary. For example, 80% of patients in the ED with chest pain do not have an acute coronary syndrome (ACS). Artificial intelligence (AI) is useful in analyzing (medical) data, and might aid health care workers in prehospital clinical decision-making before patients are presented to the hospital.

Objective

The aim of this study was to develop an AI model which would be able to predict ACS before patients visit the ED. The model retrospectively analyzed prehospital data acquired by emergency medical services' nurse paramedics.

Methods

Patients presenting to the emergency medical services with symptoms suggestive of ACS between September 20

SUBMITTER: de Koning E 

PROVIDER: S-EPMC10646678 | biostudies-literature | 2023 Oct

REPOSITORIES: biostudies-literature