Efficacy of Random Forest Models in Predicting Multidrug-Resistant Gram-Negative Bacterial Nosocomial Infections Compared to Traditional Logistic Regression Models-Reference-Cited by-同舟云学术

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Efficacy of Random Forest Models in Predicting Multidrug-Resistant Gram-Negative Bacterial Nosocomial Infections Compared to Traditional Logistic Regression Models

Published:2024-04-15 Issue: Volume: Page:
ISSN:1076-6294
Container-title:Microbial Drug Resistance
language:en
Short-container-title:Microbial Drug Resistance

Author:

Deng Jinglan¹,Ge Yongchun²,Yu Lingli³,Zuo Qiuxia¹,Zhao Kexin¹,Adila Maimaiti¹,Wang Xiao¹,Niu Ke¹,Tian Ping³⁴

Affiliation:

1. School of Nursing, Xinjiang Medical University, Urumqi, China.

2. Department of Hypertension, The Fifth Affiliated Hospital of Xinjiang Medical University, Urumqi, China.

3. Infection Management Department, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, China.

4. Health Care Research Center for Xinjiang Regional Population,Urumqi,China.

Publisher

Mary Ann Liebert Inc

Link

https://www.liebertpub.com/doi/pdf/10.1089/mdr.2023.0347

Reference39 articles.

1. Antibiotic Trends Amid Multidrug-Resistant Gram-Negative Infections in Intensive Care Units

2. Increased financial burdens and lengths of stay in patients with healthcare-associated infections due to multidrug-resistant bacteria in intensive care units: A propensity-matched case-control study

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