An Algorithm Based on Deep Learning for Predicting In‐Hospital Cardiac Arrest

An Algorithm Based on Deep Learning for Predicting In‐Hospital Cardiac Arrest

Background In‐hospital cardiac arrest is a major burden to public health, which affects patient safety. Although traditional track‐and‐trigger systems are used to predict cardiac arrest early, they have limitations, with low sensitivity and high false‐alarm rates. We propose a deep learning–based ea...

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Bibliographic Details
Main Authors: Joon‐myoung Kwon, Youngnam Lee, Yeha Lee, Seungwoo Lee, Jinsik Park
Format: Article
Language:English
Published: Wiley 2018-07-01
Series:Journal of the American Heart Association: Cardiovascular and Cerebrovascular Disease
Subjects:
artificial intelligence
cardiac arrest
deep learning
machine learning
rapid response system
resuscitation
Online Access:https://www.ahajournals.org/doi/10.1161/JAHA.118.008678

Internet

https://www.ahajournals.org/doi/10.1161/JAHA.118.008678

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