Prediction of Cardiac Arrest in the Emergency Department Based on Machine Learning and Sequential Characteristics: Model Development and Retrospective Clinical Validation Study

• Published in: JMIR medical informatics Vol. 8; no. 8; p. e15932
• Main Authors: Hong, Sungjun, Lee, Sungjoo, Lee, Jeonghoon, Cha, Won Chul, Kim, Kyunga
• Format: Journal Article
• Language: English
• Published: Toronto JMIR Publications 01.08.2020
• Subjects: Algorithms; Artificial intelligence; Blood pressure; Body temperature; Cardiac arrest; Data processing; Heart rate; Machine learning; Multimedia; Neural networks; Original Paper; Patients; Signs; Validation studies; Vital signs

Background: The development and application of clinical prediction models using machine learning in clinical decision support systems is attracting increasing attention. Objective: The aims of this study were to develop a prediction model for cardiac arrest in the emergency department (ED) using mac...