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Programming deep brain stimulation (DBS) systems currently involves a clinician manually sweeping through a range of stimulus parameter settings to identify the setting that delivers the most robust therapy for a patient. With the advent of DBS arrays with a higher number and density of electrodes, this trial and error process becomes unmanageable in a(More)
OBJECTIVE Deep brain stimulation (DBS) therapy relies on both precise neurosurgical targeting and systematic optimization of stimulation settings to achieve beneficial clinical outcomes. One recent advance to improve targeting is the development of DBS arrays (DBSAs) with electrodes segmented both along and around the DBS lead. However, increasing the(More)
Classes of hazard-odds based fixed-order and adaptive smooth goodness-of-fit tests for the composite hypothesis that an unknown discrete distribution belongs to a family of distributions using right-censored observations are presented. The proposed classes of tests generalize Neyman's 33 smooth class of tests. The class of fixed-order tests is the discrete(More)
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