Machine learning prediction of refractory ventricular fibrillation in out-of-hospital cardiac arrest using features available to EMS

Machine learning prediction of refractory ventricular fibrillation in out-of-hospital cardiac arrest using features available to EMS

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Background: Shock-refractory ventricular fibrillation (VF) or ventricular tachycardia (VT) is a treatment challenge in out-of-hospital cardiac arrest (OHCA). This study aimed to develop and validate machine learning models that could be implemented by emergency medical services (EMS) to predict refr...

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Bibliographic Details
Main Authors: Rayhan Erlangga Rahadian, Yohei Okada, Nur Shahidah, Dehan Hong, Yih Yng Ng, Michael Y.C. Chia, Han Nee Gan, Benjamin S.H. Leong, Desmond R. Mao, Wei Ming Ng, Nausheen Edwin Doctor, Marcus Eng Hock Ong
Format: Article
Language:English
Published: Elsevier 2024-06-01
Series:Resuscitation Plus
Subjects:
Machine learning
Prediction model
OHCA
ECPR
Refractory VF
Online Access:http://www.sciencedirect.com/science/article/pii/S2666520424000572

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