Exploring subtypes of multiple sclerosis through unsupervised machine learning of automated fiber quantification.

Journal: Japanese journal of radiology
PMID: 38409299

Abstract

PURPOSE: This study aimed to subtype multiple sclerosis (MS) patients using unsupervised machine learning on white matter (WM) fiber tracts and investigate the implications for cognitive function and disability outcomes.

Authors

  • Xueheng Liang
    Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, No 1 Youyi Road, Yuzhong District, Chongqing, 40016, China.
  • Zichun Yan
    Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
  • Yongmei Li
    Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.

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