Parkinson's Disease

Digital Technology for Sleep Symptoms in Parkinson's Disease: A Scoping Review.

Sleep disturbances are highly prevalent and clinically significant non-motor features of Parkinson's...

Alzheimer's and Parkinson's Detection with Video-Based Hybrid Deep Learning from Brain MRI.

Dementia, which refers to disorders related to human memory, significantly affects the human brain, ...

Machine Learning Identifies TRAPPC13/COPS5 as Biomarkers and Vesicle Transport Subtypes in Parkinson's Disease.

BACKGROUND: Parkinson's disease (PD) is a neurodegenerative disorder characterized by neuron loss an...

Geo-Mamba: Geometry-informed state-space learning of functional brain organization.

Functional magnetic resonance imaging (fMRI) derived functional connectivity (FC) is represented as ...

Classification of fallers in Parkinson's disease through machine learning based feature analysis.

Classification of fallers in Parkinson's disease (PD) is challenging due to the heterogenous motor a...

Neuromodulation of the central nervous system for facial pain.

Chronic craniofacial pain can lead to significant morbidity and reduced quality-of-life. Refractory ...

Pathology-Anchored Transcranial Sonography: A Cascaded Super-Resolution Deep Learning System for Early-Stage Parkinson's Disease Grading.

Delayed diagnosis of Parkinson's disease (PD) due to undetectable early pathological changes remains...

A graph deep learning method for diagnosis of Parkinson's disease using brain functional connectivity features.

Early and precise identification of Parkinson's disease (PD) is crucial for clinical intervention. R...

Classification of functional brain patterns elicited by deep brain stimulation of the subthalamic nucleus in Parkinson's disease.

Despite the remarkable success of deep brain stimulation (DBS) in alleviating Parkinson's disease (P...

Leveraging machine learning to predict Parkinson's disease using pre-symptomatic proteomics data.

In Parkinson's disease, non-motor symptoms precede the characteristic motor manifestations by up to ...

Quantitative susceptibility mapping and MRS-based multimodal machine learning for early Parkinson's disease classification.

Parkinson's disease (PD) is a complex, progressive neurodegenerative disorder characterized by high ...

Focused ultrasound thalamotomy improves voice tremor in essential tremor: objective insight from artificial intelligence.

An enhanced framework for Parkinson's disease severity prediction using improved optimization in multi-scale TCN.

RESEARCH BACKGROUND: Parkinson's Disease (PD) requires accurate severity prediction models for enabl...

Preoperative functional connectivity patterns predict tremor relief following MRgFUS thalamotomy in essential tremor: A machine learning investigation.

BACKGROUND: Magnetic resonance-guided focused ultrasound (MRgFUS) thalamotomy made a breakthrough in...

AI-Driven Multimodal Analysis of Neuroimaging and Speech Data for Diagnosis of Alzheimer's, Parkinson's, and Epilepsy.

This study investigates the application of machine learning (ML) techniques combined with neuroimagi...

Integrating Eye Tracking and Inertial Sensing for Enhanced Freezing of Gait Detection in Parkinson's Disease.

Freezing of gait (FOG), a disabling symptom in Parkinson's disease, presents a major challenge for w...

Predicting Long-Term Depression Progression in Parkinson's Disease: A Machine-Learning Survival Analysis and Risk Score.

BACKGROUND: Depression in Parkinson's disease (dPD) is common and heterogeneous, impairs quality of ...

Perspective: Depression in Persons with Parkinson's Disease.

Depression is a prevalent and disabling syndrome characterized by sustained sadness and/or anhedonia...

Efficient Voice-Based Parkinson Classification via Algorithm-Level Class Balancing.

Parkinson's disease (PD) is a progressive neurodegenerative disorder, and the diagnostic procedures ...

Enhancing Parkinson's Disease Staging: An Integrative Deep Learning Framework for Multimodal Feature Selection.

Parkinson's disease (PD) affects 10 million globally, with accurate staging essential for personaliz...

Machine learning prediction of discharge destination in patients with Parkinson's disease; a nationwide cohort study.

Risk stratification during hospitalization may support real-world discharge planning. We developed a...