Development and Validation of Machine Learning-Based Models to Predict In-Hospital Mortality in Life-Threatening Ventricular Arrhythmias: Retrospective Cohort Study
BackgroundLife-threatening ventricular arrhythmias (LTVAs) are main causes of sudden cardiac arrest and are highly associated with an increased risk of mortality. A prediction model that enables early identification of the high-risk individuals is still lacking. ObjectiveWe aimed to build machine le...
Saved in:
Main Authors: | Le Li (Author), Ligang Ding (Author), Zhuxin Zhang (Author), Likun Zhou (Author), Zhenhao Zhang (Author), Yulong Xiong (Author), Zhao Hu (Author), Yan Yao (Author) |
---|---|
Format: | Book |
Published: |
JMIR Publications,
2023-11-01T00:00:00Z.
|
Subjects: | |
Online Access: | Connect to this object online. |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Electrocardiographic tracking of left ventricular hypertrophy in hypertension: incidence and prognostic outcomes from the SPRINT trial
by: Zhuxin Zhang, et al.
Published: (2024) -
Causal effects between atrial fibrillation and heart failure: evidence from a bidirectional Mendelian randomization study
by: Zhuxin Zhang, et al.
Published: (2023) -
Can chronotropic incompetence predict life-threatening ventricular arrhythmias in patients with stable ischemic heart disease?
by: Yelena Rib, et al.
Published: (2018) -
Ventricular arrhythmia: A feature of tubercular myocarditis
by: Neeraj Awasthy, et al.
Published: (2019) -
Electrical Signs predictors of malignant ventricular arrhythmias.
by: Ailema Amelia Alemán Fernández, et al.
Published: (2012)