From Images to Insights: Subtyping Parkinson’s Disease Using Unsupervised Learning on MRI Data
Objective: To explore the heterogeneity of Parkinson's disease (PD) using unsupervised clustering of neuroimaging data, aiming to identify distinct subtypes based on volumetric features. Background:…Regional Brain Volume Differences Across PD Clinical Subtypes
Objective: To investigate brain morphometric differences across Parkinson disease (PD) clinical subtypes. Background: We developed a PD subtype classification with three subtypes that includes motor…Deep brain stimulation Intraoperative imaging: False errors in the era of artificial intelligence
Objective: To assess the precision of Deep Brain Stimulation (DBS) electrode placement within Subthalamic nucleus (STN) using Advanced Imaging and artificial intelligence, considering the challenges…Deposition of phosphorylated TDP-43 around the tip of deep brain stimulation leads
Objective: The objective of this study is to investigate the depositions of abnormal proteins, including phosphorylated tau (p-tau) and phosphorylated transactivation response DNA-binding protein of…Evaluation of the results of neuromodulation of the Subthalamic Nucleus (STN) in patients with Parkinson’s Disease (PD) depending on the anesthesia used during stereotactic electrode implantation.
Objective: Comparison of the efficacy of STN neuromodulation after surgical intervention with Monitored Anesthesia Care (MAC) and using general anesthesia (GA). Background: The effectiveness of…MRgFUS thalamotomy for tremor-predominant Parkinson´s disease: a single-center prospective study
Objective: To examine the clinical outcomes and their relationship with lesion characteristics at 6-month follow-up in TDPD patients Background: Clinical outcomes and lesion features after…Artificial Intelligence and Visual Analysis of Movements in Parkinson’s Disease
Objective: To evaluate the use of artificial intelligence in the analysis and classification of movements in Parkinson's disease. Background: Artificial intelligence (AI) is a powerful…Automatic detection of Freezing of gait in Parkinson’s disease with IMU: validation of a deep learning algorithm in the home.
Objective: To validate a deep learning (DL) algorithm to detect Freezing of gait (FOG) at home. Background: FOG is an episodic gait symptom of Parkinson’s…Wearable sensors and AI in Parkinson’s disease – How continuous symptom and treatment response monitoring can enable better clinical decision making – Interim results from an observational study
Objective: To investigate how continuous objective information on motor symptoms and treatment response combined with subjective patient reported insights can be used to optimize Parkinson’s…REM sleep behavior disorder and Prodromal Parkinson’s Disease in patients with Essential Tremor
Objective: To assess the prevalence of REM sleep behaviour disorder (RBD) and Prodromal Parkinson's Disease (PPD) in Essential Tremor (ET) and to characterize these sub-groups…
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