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Research on Mortality Prediction Model of NSICU Patients Based on Machine Learning

Author

Listed:
  • Xue Feng

    (Beijing Jiaotong University)

  • Shifeng Liu

    (Beijing Jiaotong University)

Abstract

ICU (Intensive Care Unit) provides isolation places and equipment for severely ill or unconscious patients, and provides services such as the best nursing, comprehensive treatment, and early postoperative rehabilitation. A large amount of data is generated every day in the ICU, including demographic information, admission examination, diagnosis, medication and other information. We establish a prediction model for NSICU (Neurosurgical Intensive Care Unit) patient using machine learning. In this paper, we choose five classical model to determine the mortality prediction model of NSICU patients. In order to alleviate the problem of class imbalance, this article resamples the sample to eliminate the impact of this problem based on SMOTEENN. In addition, use the SHapley Additive explanation (SHAP) interpreter to illustrate the relationship between predictive variables and the results, which is helpful for doctors to make decisions.

Suggested Citation

  • Xue Feng & Shifeng Liu, 2025. "Research on Mortality Prediction Model of NSICU Patients Based on Machine Learning," Lecture Notes in Operations Research,, Springer.
    • Handle: RePEc:spr:lnopch:978-981-96-9697-0_67
    DOI: 10.1007/978-981-96-9697-0_67
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