A Machine Learning Prediction Model for Non-cardiogenic Out-of-hospital Cardiac Arrest with Initial Non-shockable Rhythm
Author:
Affiliation:
1. Department of Emergency and Critical Care Medicine, Juntendo University Urayasu Hospital
Publisher
The Jutendo Medical Journal
Subject
General Agricultural and Biological Sciences
Link
https://www.jstage.jst.go.jp/article/jmj/69/3/69_JMJ22-0035-OA/_pdf
Reference17 articles.
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2. [2] Sidey-Gibbons JAM, Sidey-Gibbons CJ: Machine learning in medicine: a practical introduction. BMC Med Res Methodol. 2019; 19: 64.
3. [3] Nakashima T, Ogata S, Noguchi T, et al: Machine learning model for predicting out-of-hospital cardiac arrests using meteorological and chronological data. Heart. 2021; 107: 1084-1091.
4. [4] Cheng CY, Chiu IM, Zeng WH, Tsai CM, Lin CHR: Machine Learning Models for Survival and Neurological Outcome Prediction of Out-of-Hospital Cardiac Arrest Patients. Biomed Res Int. 2021; 2021: 9590131.
5. [5] Hirano Y, Kondo Y, Sueyoshi K, Okamoto K, Tanaka H: Early outcome prediction for out-of-hospital cardiac arrest with initial shockable rhythm using machine learning models. Resuscitation. 2021; 158: 49-56.
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1. Out-of-Hospital Cardiac Arrest Prognostics Modelling using Machine Learning Techniques;2023 IEEE International Conference on Computing (ICOCO);2023-10-09
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