Abstract
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.
Original language | English |
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Number of pages | 1 |
Publication status | Published - Aug 2020 |
Event | 2020 ISMRM & SMRT Virtual Conference and Exhibition - Virtual Duration: 8 Aug 2020 → 14 Aug 2020 |
Conference
Conference | 2020 ISMRM & SMRT Virtual Conference and Exhibition |
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Period | 8/08/20 → 14/08/20 |