Use of machine learning models to predict neurologically intact survival for advanced age adults following out-of-hospital cardiac arrest

IF 3.4 3区医学 Q1 EMERGENCY MEDICINE

Academic Emergency Medicine Pub Date : 2024-09-19 DOI:10.1111/acem.15018

Kameshwari Soundararajan, Dylana J. Adams, Brian H. Nathanson, Timothy J. Mader, Ryan C. Godwin, Ryan L. Melvin, Ryan A. Coute

引用次数: 0

Abstract

CONFLICT OF INTEREST STATEMENT

The authors declare no conflicts of interest.

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使用机器学习模型预测院外心脏骤停后高龄成人神经功能完好的存活率

利益冲突声明作者声明没有利益冲突。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Academic Emergency Medicine 医学-急救医学

CiteScore

7.60

自引率

6.80%

发文量

207

审稿时长

3-8 weeks

期刊介绍： Academic Emergency Medicine (AEM) is the official monthly publication of the Society for Academic Emergency Medicine (SAEM) and publishes information relevant to the practice, educational advancements, and investigation of emergency medicine. It is the second-largest peer-reviewed scientific journal in the specialty of emergency medicine. The goal of AEM is to advance the science, education, and clinical practice of emergency medicine, to serve as a voice for the academic emergency medicine community, and to promote SAEM''s goals and objectives. Members and non-members worldwide depend on this journal for translational medicine relevant to emergency medicine, as well as for clinical news, case studies and more. Each issue contains information relevant to the research, educational advancements, and practice in emergency medicine. Subject matter is diverse, including preclinical studies, clinical topics, health policy, and educational methods. The research of SAEM members contributes significantly to the scientific content and development of the journal.