Novel gene signatures predicting and immune infiltration analysis in Parkinson's disease: based on combining random forest with artificial neural network.

Journal: Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology
Published Date: Jun 1, 2024

Abstract

BACKGROUND: Parkinson's disease (PD) ranks as the second most prevalent neurodegenerative disorder globally, and its incidence is rapidly rising. The diagnosis of PD relies on clinical characteristics. Although current treatments aim to alleviate symptoms, they do not effectively halt the disease's progression. Early detection and intervention hold immense importance. This study aimed to establish a new PD diagnostic model.

Authors

  • Shucai Xie
    Department of Critical Care Medicine, National Clinical Research Center for Genetic Disorders, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, China.
  • Pei Peng
    Department of Medicine Oncology, Changde Hospital, Xiangya School of Medicine, Central South University (The first people's hospital of Changde city), Changde, China.
  • Xingcheng Dong
    Department of Orthopedics, Changde Hospital, Xiangya School of Medicine, Central South University (The first people's hospital of Changde city), Changde, China.
  • Junxing Yuan
    Department of Neurology, Changde Hospital, Xiangya School of Medicine, Central South University (The first people's hospital of Changde city), No. 818 Renmin Road, Changde, 415000, Hunan, China.
  • Ji Liang
    Tianjin University, School of Materials Science and Engineering, Bldg 31, Tianjin, CHINA.

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