Our results suggest that slight improvements in accuracy can be observed (see Table 3 ), and that different artifact rejection approaches (i.e., EXP, COV [ 13 , 14 ], and BCK [ 15 , 16 ]) can similarly improve MER classification compared to not removing them at all, but this improvement did not reach statistical significance.
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The Role of MER Processing Pipelines for STN Functional Identification During DBS Surgery: A Feature-Based Machine Learning Approach.
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