Leveraging diverse cell-death patterns in diagnosis of sepsis by integrating bioinformatics and machine learning.

Journal: PeerJ
PMID: 40028203

Abstract

BACKGROUND: Sepsis is a life-threatening disease causing millions of deaths every year. It has been reported that programmed cell death (PCD) plays a critical role in the development and progression of sepsis, which has the potential to be a diagnosis and prognosis indicator for patient with sepsis.

Authors

  • Mi Liu
    Department of Digital Image in Sangmyung University, Seoul 03015, Republic of Korea.
  • Xingxing Gao
    Department of Thyroid Surgery, The First Affiliated Hospital, Zhejiang University School of Medicine, Hang Zhou, China.
  • Hongfa Wang
    Center for Rehabilitation Medicine, Department of Anesthesiology, Zhejiang Provincial People's Hospital, Affiliated People's Hospital, Hangzhou Medical College, Hang Zhou, China.
  • Yiping Zhang
    College of Electrical Engineering, Zhengzhou University, Zhengzhou 450001, PR China.
  • Xiaojun Li
    Jiangsu CM Clinical Innovation Center of Degenerative Bone & Joint Disease, Wuxi TCM Hospital Affiliated to Nanjing University of Chinese Medicine, Wuxi, China.
  • Renlai Zhu
    Center for Rehabilitation Medicine, Department of Anesthesiology, Zhejiang Provincial People's Hospital, Affiliated People's Hospital, Hangzhou Medical College, Hang Zhou, China.
  • Yunru Sheng
    Center for Rehabilitation Medicine, Department of Anesthesiology, Zhejiang Provincial People's Hospital, Affiliated People's Hospital, Hangzhou Medical College, Hang Zhou, China.

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