Deep learning-based Emergency Department In-hospital Cardiac Arrest Score (Deep EDICAS) for early prediction of cardiac arrest and cardiopulmonary resuscitation in the emergency department

Deep learning-based Emergency Department In-hospital Cardiac Arrest Score (Deep EDICAS) for early prediction of cardiac arrest and cardiopulmonary resuscitation in the emergency department

Abstract Background Timely identification of deteriorating patients is crucial to prevent the progression to cardiac arrest. However, current methods predicting emergency department cardiac arrest are primarily static, rule-based with limited precision and cannot accommodate time-series data. Deep l...

Full description

Saved in:
Bibliographic Details
Main Authors: Yuan-Xiang Deng, Jyun-Yi Wang, Chia-Hsin Ko, Chien-Hua Huang, Chu-Lin Tsai, Li-Chen Fu
Format: Article
Language:English
Published: BMC 2024-11-01
Series:BioData Mining
Subjects:
Emergency department
Cardiac arrest
Early warning system
Multi-modal model
Time series data
Online Access:https://doi.org/10.1186/s13040-024-00407-8
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://doi.org/10.1186/s13040-024-00407-8

Similar Items