Machine learning prediction models for in-hospital postoperative functional outcome after moderate-to-severe traumatic brain injury.

Journal: European journal of trauma and emergency surgery : official publication of the European Trauma Society
PMID: 38355915

Abstract

AIM: This study aims to utilize machine learning (ML) and logistic regression (LR) models to predict surgical outcomes among patients with traumatic brain injury (TBI) based on admission examination, assisting in making optimal surgical treatment decision for these patients.

Authors

  • An-An Yin
    Department of Plastic and Reconstructive Surgery, Department of Neurosurgery, Xijing Hospital, Fourth Military Medical University, Xi'an, Shaanxi, China.
  • Xi Zhang
    The First Clinical Medical College, Guangxi University of Chinese Medicine, Nanning 530001, China.
  • Ya-Long He
    Department of Neurosurgery, Xijing Institute of Clinical Neuroscience, Xijing Hospital, Fourth Military Medical University, Changle West Road, No. 169, Xi'an, 710032, China.
  • Jun-Jie Zhao
    Department of Neurosurgery, Xijing Institute of Clinical Neuroscience, Xijing Hospital, Fourth Military Medical University, Changle West Road, No. 169, Xi'an, 710032, China.
  • Xiang Zhang
    Department of Orthopedics, Orthopedic Research Institute, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
  • Zhou Fei
    Department of Neurosurgery, Xijing Institute of Clinical Neuroscience, Xijing Hospital, Fourth Military Medical University, Changle West Road, No. 169, Xi'an, 710032, China. fzneuro@126.com.
  • Wei Lin
    Department of Geriatric Rehabilitation, Jiangbin Hospital, Nanning, China.
  • Bao-Qiang Song
    Department of Plastic and Reconstructive Surgery, Craniomaxillofacial Surgery Group, Xijing Hospital, Fourth Military Medical University, Changle West Road, No. 169, Xi'an, 710032, China. songbq@fmmu.edu.cn.

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