Machine Learning of Laboratory Data in Predicting 30-Day Mortality for Adult Hemophagocytic Lymphohistiocytosis.

Journal: Journal of clinical immunology
PMID: 39302504

Abstract

BACKGROUND: Hemophagocytic Lymphohistiocytosis (HLH) carries a high mortality rate. Current existing risk-evaluation methodologies fall short and improved predictive methods are needed. This study aimed to forecast 30-day mortality in adult HLH patients using 11 distinct machine learning (ML) algorithms.

Authors

  • Jun Zhou
    Department of Clinical Research Center, Dazhou Central Hospital, Dazhou 635000, China.
  • Mengxiao Xie
    Department of Laboratory Medicine, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China.
  • Ning Dong
    Jinling Clinical Medical College, Nanjing Medical University，Nanjing，Jiangsu 210002，China.
  • Mingjun Xie
    Department of Laboratory Medicine, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China.
  • Jingping Liu
    Department of Laboratory Medicine, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China.
  • Min Wang
    National and Local Joint Engineering Research Center of Ecological Treatment Technology for Urban Water Pollution, Wenzhou University, Wenzhou 325035, China.
  • Yaman Wang
    Department of Laboratory Medicine, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China.
  • Hua-Guo Xu
    Department of Laboratory Medicine, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China. huaguoxu@njmu.edu.cn.

Keywords

External Resources

Popular Topics
Recent Journals