Parkinson's disease (PD) is a common neurodegenerative disorder characterized by disabling motor and non-motor symptoms.1 The abnormalities of white-matter (WM) tracts/regions have been demonstrated in PD. However, previous studies have largely dependent on univariate analysis, such as t-test, which may result in Type-1 error. Further, it remains unclear whether the disruption of WM tracts/regions provided worthwhile information to identify PD from HC. Hence, in current study, a machine learning approach was applied to investigate the white matter profiles of PD.
|Number of pages||1|
|Publication status||Published - Aug 2020|
|Event||2020 ISMRM & SMRT Virtual Conference and Exhibition - Virtual event|
Duration: 8 Aug 2020 → 14 Aug 2020
|Conference||2020 ISMRM & SMRT Virtual Conference and Exhibition|
|Period||8/08/20 → 14/08/20|