Identification of key genes and development of an identifying machine learning model for sepsis.

Journal: Inflammation research : official journal of the European Histamine Research Society ... [et al.]
Published Date: Jun 30, 2025

Abstract

OBJECTIVE AND DESIGN: This study aims to identify key genes of sepsis and construct a model for sepsis identification through integrated multi-organ single-cell RNA sequencing (scRNA-seq) and machine learning.

Authors

  • Zhonghao Li
    Department of Neurosurgery, Dongfang Hospital, Beijing University of Chinese Medicine, Beijing, China.
  • Shengsong Chen
    Department of Pulmonary and Critical Care Medicine, The First Affiliated Hospital of Nanchang University, Nanchang, China.
  • Nan Gao
    Department of Biological Sciences, Rutgers University, Newark, NJ, USA.
  • Jie Chen
    School of Basic Medical Sciences, Health Science Center, Ningbo University, Ningbo, China.
  • Ying Qin
    School of Economics and Management, Wuhan University, Bayi Road No.299, Wuchang District, Wuhan, 430072, China. qy1119@163.com.
  • Guoqiang Zhang
    Department of Orthopeadics, The First Medical Centre, Chinese PLA General Hospital, Beijing, China.

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