Deep learning-based Prediction of Gait Dysfunction in Parkinson’s Disease using Quantitative Diffusion MRI from Brain Network Regions of Interest
Objective: Compare the performance of two deep learning models trained on quantitative diffusion measurements from brain network ROIs in the prediction of gait dysfunction in…Real-world Programming and Sensing from Adaptive Deep Brain Stimulation for Parkinson’s Disease in Japan
Objective: To characterize programming configurations and local field potentials (LFP) control parameters in a multicenter, real-world cohort of patients receiving deep brain stimulation (DBS) for…Acute and chronic effects of deep brain stimulation on gait in patients with Parkinson’s disease.
Objective: To investigate the acute and chronic effects of deep brain stimulation (DBS) of subthalamic nucleus (STN) or globus pallidus internus (GPi) on gait in…Bilateral subthalamic nucleus deep brain stimulation as effective and sustained therapy in Juvenile Parkinson’s disease due to PTPA gene mutations
Objective: To report the efficacy of bilateral subthalamic nucleus (STN) Deep Brain Stimulation (DBS) in two siblings with Juvenile Parkinson’s Disease (JP) due to homozygous…A Conversational GPT Agent for Parkinson’s Disease
Objective: To create a conversational chat agent that can provide persons with Parkinson’s with information about their disease. Background: Artificial intelligence using Large Language Models…Reliability of real-world walking activity and gait assessment in people with Parkinson’s disease – how many hours and days are needed?
Objective: To define i) the minimally required daily wear time during waking hours that constitutes a valid measurement of walking using digital mobility outcomes (DMOs)…Prediction of falls in PD over 5 years using kinematic data and machine learning
Objective: This study aims to evaluate the potential of a wearable sensor-based walking and balance assessment to predict the risk of falling in individuals with…Distinguishing Parkinson’s disease from atypical Parkinsonian syndrome using multistage deep learning based on dopamine transporter imaging
Objective: We made the diagnostic model using a deep learning algorithm based on dopamine transporterWe made the diagnostic model using a deep learning algorithm based…Candidate biomarkers of EV-microRNA in detecting REM sleep behavior disorder and Parkinson’s disease
Objective: Accessible and reliable biomarkers for early diagnosis of PD and iRBD are urgently needed to identify candidate therapeutic targets and to monitor disease progression…Association between Genetic Polymorphisms and Disease Progression in Parkinson’s disease
Objective: In this study, we aim to elucidate the association between the various haplotypes of the Catechol-O-methyltransferase (COMT) and Monoamine oxidase B (MAO-B) genes, the…
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