A Machine learning model for predicting sepsis based on an optimized assay for microbial cell-free DNA sequencing.

Journal: Clinica chimica acta; international journal of clinical chemistry
PMID:

Abstract

OBJECTIVE: To integrate an enhanced molecular diagnostic technique to develop and validate a machine-learning model for diagnosing sepsis.

Authors

  • Lili Wang
    School of Logistics, Chengdu University of Information Technology, Chengdu, China.
  • Wenjie Tian
    Department of Laboratory Medicine, Shanghai East Hospital, Tongji University School of Medicine, Shanghai, China.
  • Weijun Zhang
    Shanghai United Imaging Healthcare Co., Ltd., Shanghai, China.
  • Donghua Wen
    Department of Laboratory Medicine, Shanghai East Hospital, Tongji University School of Medicine, Shanghai, China.
  • Simin Yang
    Department of Laboratory Medicine, Shanghai East Hospital, Tongji University School of Medicine, Shanghai, China.
  • Jichao Wang
    School of International Education, Anyang Institute of Technology, Anyang, China.
  • Xu Han
  • Jun Wang
    Department of Speech, Language, and Hearing Sciences and the Department of Neurology, The University of Texas at Austin, Austin, TX 78712, USA.
  • Wenchao Ding
    Matridx Biotechnology Co., Ltd, Hangzhou, China.
  • Lihui Wang
    Shanghai Mental Health Center, Shanghai Jiao Tong University, School of Medicine, Shanghai, China.
  • Yuetian Yu
    Department of Critical Care Medicine, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
  • Wenjuan Wu
    School of Traditional Chinese Medicine, Capital Medical University, Beijing 100069, China; College of Science, China Agricultural University, Beijing 100193, China.