Leveraging machine learning for precision medicine: a predictive model for cognitive impairment in cholestasis patients.

Journal: BMC gastroenterology
PMID: 40102737

Abstract

BACKGROUND: Cholestasis, characterized by impaired bile flow, impacts cognitive function through systemic mechanisms, including inflammation and metabolic dysregulation. Despite its significance, targeted predictive models for cognitive impairment in cholestasis remain underexplored. This study addresses this gap by developing a machine learning-based predictive model tailored to this population.

Authors

  • Caixia Fang
    Department of Pharmacy, Qingyang City People's Hospital, Qingyang, China.
  • Lina Zhang
    Intensive Care Unit, XiangYa Hospital, Central South University, Changsha, China.
  • Lanlan Xu
    Department of Pharmacy, Clinical Trial Research Center of Qingyang People's Hospital, Qingyang, Gansu, China.
  • Yongsheng He
    State Key Laboratory of Mechanics and Control of Mechanical Structures, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, P. R. China.
  • Xuerong Zhang
    Clinical Trial Research Center, Qingyang People's Hospital, Qingyang, Gansu, China.
  • Xiaojuan Xing
    Department of Neurology, Qingyang People's Hospital, Qingyang, Gansu, China. 59984456@qq.com.

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