The application value of Rs-fMRI-based machine learning models for differentiating mild cognitive impairment from Alzheimer's disease: a systematic review and meta-analysis.

Journal: Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology
Published Date: Sep 3, 2024

Abstract

BACKGROUND: Various machine learning (ML) models based on resting-state functional MRI (Rs-fMRI) have been developed to facilitate differential diagnosis of mild cognitive impairment (MCI) and Alzheimer's disease (AD). However, the diagnostic accuracy of such models remains understudied. Therefore, we conducted this systematic review and meta-analysis to explore the diagnostic accuracy of Rs-fMRI-based radiomics in differentiating MCI from AD.

Authors

  • Chentong Wang
    Rheumatology Immunology Department, Ningbo Medical Center Lihuili Hospital, Ningbo, Zhejiang, 315000, China.
  • Li Zhou
    School of Education, China West Normal University, Nanchong, Sichuan, China.
  • Feng Zhou
    Department of Urology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China.
  • Tingting Fu
    School of Mechanical Engineering, Southwest Jiaotong University, Chengdu 610031, China.

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