A Machine Learning-Based Approach to Predict Prognosis and Length of Hospital Stay in Adults and Children With Traumatic Brain Injury: Retrospective Cohort Study.

Journal: Journal of medical Internet research
PMID: 36485032

Abstract

BACKGROUND: The treatment and care of adults and children with traumatic brain injury (TBI) constitute an intractable global health problem. Predicting the prognosis and length of hospital stay of patients with TBI may improve therapeutic effects and significantly reduce societal health care burden. Applying novel machine learning methods to the field of TBI may be valuable for determining the prognosis and cost-effectiveness of clinical treatment.

Authors

  • Cheng Fang
    Centre for Environmental Risk Assessment and Remediation, University of South Australia, Mawson Lakes, SA 5095, Australia; CRC for Contamination Assessment and Remediation of Environment, Mawson Lakes Boulevard, Mawson Lakes, SA 5095, Australia.
  • Yifeng Pan
    The School of Big Data and Artificial Intelligence, Anhui Xinhua University, Hefei, China.
  • Luotong Zhao
    Department of Neurosurgery, The Second Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, China.
  • Zhaoyi Niu
    Department of Neurosurgery, The Second Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, China.
  • Qingguo Guo
    Department of Neurosurgery, The Second Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, China.
  • Bing Zhao
    Department of Neurology, Changzhi People's Hospital, Changzhi Medical College, Changzhi, China.

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