Machine learning and bioinformatics analysis of diagnostic biomarkers associated with the occurrence and development of lung adenocarcinoma.

Journal: PeerJ
Published Date: Jul 23, 2024

Abstract

OBJECTIVE: Lung adenocarcinoma poses a major global health challenge and is a leading cause of cancer-related deaths worldwide. This study is a review of three molecular biomarkers screened by machine learning that are not only important in the occurrence and progression of lung adenocarcinoma but also have the potential to serve as biomarkers for clinical diagnosis, prognosis evaluation and treatment guidance.

Authors

  • Yong Li
    Department of Surgical Sciences, Western Michigan University Homer Stryker M.D. School of Medicine, Kalamazoo, MI, United States.
  • Yunxiang Cai
    Department of Clinical Laboratory, The First Affiliated Hospital of Huzhou University, The First People's Hospital of Huzhou City, Zhejiang Province, China.
  • Longfei Ji
    Department of Clinical Laboratory, The First Affiliated Hospital of Huzhou University, The First People's Hospital of Huzhou City, Zhejiang Province, China.
  • Binyu Wang
    Department of Clinical Laboratory, The First Affiliated Hospital of Huzhou University, The First People's Hospital of Huzhou City, Zhejiang Province, China.
  • Danfei Shi
    Department of Pathology, The First Affiliated Hospital of Huzhou University, The First People's Hospital of Huzhou City, Zhejiang Province, China.
  • Xinmin Li
    Department of Clinical Laboratory, Chongqing Hospital of Traditional Chinese Medicine, Chongqing, China.

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