Application of multi-feature-based machine learning models to predict neurological outcomes of cardiac arrest

Application of multi-feature-based machine learning models to predict neurological outcomes of cardiac arrest

Cardiac arrest (CA) is a major disease burden worldwide and has a poor prognosis. Early prediction of CA outcomes helps optimize the therapeutic regimen and improve patients’ neurological function. As the current guidelines recommend, many factors can be used to evaluate the neurological outcomes of...

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Bibliographic Details
Main Authors: Peifeng Ni, Sheng Zhang, Wei Hu, Mengyuan Diao
Format: Article
Language:English
Published: Elsevier 2024-12-01
Series:Resuscitation Plus
Subjects:
Cardiac arrest
Neurological outcomes
Machine learning
Electronic Health Records
Biomarkers
Imaging
Online Access:http://www.sciencedirect.com/science/article/pii/S2666520424002807
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