Prediction of carbapenem-resistant gram-negative bacterial bloodstream infection in intensive care unit based on machine learning.

Journal: BMC medical informatics and decision making
PMID: 38745177

Abstract

BACKGROUND: Predicting whether Carbapenem-Resistant Gram-Negative Bacterial (CRGNB) cause bloodstream infection when giving advice may guide the use of antibiotics because it takes 2-5 days conventionally to return the results from doctor's order.

Authors

  • Qiqiang Liang
    General Intensive Care Unit and Key Laboratory of Multiple Organ Failure, China National Ministry of Education, Second Affiliated Hospital of Zhejiang University School of Medicine, No. 1511, Jianghong Road, Bingjiang District, Hangzhou, Zhejiang, China.
  • Shuo Ding
    Department of Biomedical Engineering, National University of Singapore, Singapore.
  • Juan Chen
    Department of Occupational and Environmental Health Sciences, School of Public Health, Peking University, Beijing 100191, China. chenjuan94@bjmu.edu.cn.
  • Xinyi Chen
    School of Electronic and Electrical Engineering, Shanghai University of Engineering Science, Shanghai 201620, China. Electronic address: c2257873708@163.com.
  • Yongshan Xu
    General Intensive Care Unit and Key Laboratory of Multiple Organ Failure, China National Ministry of Education, Second Affiliated Hospital of Zhejiang University School of Medicine, No. 1511, Jianghong Road, Bingjiang District, Hangzhou, Zhejiang, China.
  • Zhijiang Xu
    Clinical Laboratory, Second Affiliated Hospital of Zhejiang University, Hangzhou, Zhejiang, China.
  • Man Huang
    General Intensive Care Unit and Key Laboratory of Multiple Organ Failure, China National Ministry of Education, Second Affiliated Hospital of Zhejiang University School of Medicine, No. 1511, Jianghong Road, Bingjiang District, Hangzhou, Zhejiang, China. huangman@zju.edu.cn.

Keywords

External Resources

Popular Topics
Recent Journals