[Comparison of the predictive performance of Logistic regression, BP neural network and support vector machine model for the risk of acute exacerbation of readmission in elderly patients with chronic obstructive pulmonary disease within 30 days].

Journal: Zhonghua wei zhong bing ji jiu yi xue
Published Date: Aug 1, 2022

Abstract

OBJECTIVE: To compare the effectiveness of Logistic regression, BP neural network and support vector machine models in the prediction of 30-day risk of readmission in elderly patients with an exacerbation of chronic obstructive pulmonary disease (COPD) and to provide a scientific basis for the screening and prevention of high-risk patients with readmission.

Authors

  • Rui Zhang
    Department of Cardiology, Zhongda Hospital, Medical School of Southeast University, Nanjing, China.
  • Yan Chang
    Department of Nursing, the General Hospital of Ningxia Medical University, Yinchuan 750004, Ningxia Hui Autonomous Region, China.
  • Xiaona Zhang
    Department of Nursing, the General Hospital of Ningxia Medical University, Yinchuan 750004, Ningxia Hui Autonomous Region, China.
  • Lu Lu
    China School of Traditional Chinese Medicine, Southern Medical University, Guangzhou, 510515, China.
  • Ling Ding
    Zhejiang Province Key Laboratory of Anti-Cancer Drug Research, Institute of Pharmacology and Toxicology, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China.
  • Hongyan Lu
    Department of Nursing, the General Hospital of Ningxia Medical University, Yinchuan 750004, Ningxia Hui Autonomous Region, China.

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