[Application of support vector machine in predicting in-hospital mortality risk of patients with acute kidney injury in ICU].

Journal: Beijing da xue xue bao. Yi xue ban = Journal of Peking University. Health sciences
Published Date: Apr 18, 2018

Abstract

OBJECTIVE: To construct an in-hospital mortality prediction model for patients with acute kidney injury (AKI) in intensive care unit (ICU) by using support vector machine (SVM), and compare it with the simplified acute physiology score II (SAPS-II) which is commonly used in the ICU.

Authors

  • K Lin
    Department of Epidemiology and Biostatistics, Peking University School of Public Health, Beijing 100191, China; Medical Informatics Center, Peking University, Beijing 100191, China.
  • J Q Xie
    Department of Epidemiology and Biostatistics, Peking University School of Public Health, Beijing 100191, China; Medical Informatics Center, Peking University, Beijing 100191, China.
  • Y H Hu
    Department of Epidemiology and Biostatistics, Peking University School of Public Health, Beijing 100191, China; Medical Informatics Center, Peking University, Beijing 100191, China.
  • G L Kong
    Medical Informatics Center, Peking University, Beijing 100191, China.

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