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Determining and Leveraging Local Ancestry to Assess Individual-Level Risk: from the Global Parkinson’s Genetics Program
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Determining Cerebrospinal Fluid Alpha-Synuclein Seed Amplification Assay Status from Demographics and Clinical Data
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Determining the Direction of segmented DBS Micro Electrodes through the EEG
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Determining the optimal filtering method for the removal of gait-related movement artefacts from EEG acquired from People with Parkinson’s Disease
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Developing a selection framework for digital measures of Parkinson’s disease progression for the EJS ACT-PD trial
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Developing a Supervised Machine Learning Model for Long-Term Cognitive Status Prediction in Parkinson Disease
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Developing a Supportive Care and Wellness Program for Parkinson’s Patients
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Developing a Virtual Brick-Building Group for Veterans with Movement Disorders
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Developing Composite Digital Measures for Tracking Parkinson’s Disease (PD) Progression using a Comprehensive Machine Learning-based Framework
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Developing composite measures that track physical activity change in people with early-stage Parkinson’s disease using machine learning and wearable sensors
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