Neurology

Parkinson's Disease

Latest AI and machine learning research in parkinson's disease for healthcare professionals.

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Baseline [F]FP-CIT PET-based deep learning prediction of levodopa-induced dyskinesia in Parkinson's disease.

We aimed to develop a convolutional neural network (CNN) model with multi-task learning to predict t...

Lipid nanoparticle (LNP) mediated mRNA delivery in neurodegenerative diseases.

Neurodegenerative diseases (NDD) are characterized by the progressive loss of neurons and the impair...

AI-Driven Advances in Parkinson's Disease Neurosurgery: Enhancing Patient Selection, Trial Efficiency, and Therapeutic Outcomes.

Parkinson's disease (PD) is a progressive neurodegenerative disorder marked by motor and non-motor d...

Deep learning for Parkinson's disease classification using multimodal and multi-sequences PET/MR images.

BACKGROUND: We aimed to use deep learning (DL) techniques to accurately differentiate Parkinson's di...

Identifying Common Disease Trajectories of Progressive Supranuclear Palsy with Electronic Health Records.

BACKGROUND: Progressive supranuclear palsy (PSP) is a rare neurodegenerative disorder characterized ...

A Multi-Modal Graph Neural Network Framework for Parkinson's Disease Therapeutic Discovery.

Parkinson's disease (PD) is a complex neurodegenerative disorder lacking effective disease-modifying...

A new network structure for Parkinson's handwriting image recognition.

Parkinson's disease (PD) remains a condition without a cure, though its early manifestations can be ...

Machine Learning Predicts Risk of Falls in Parkison's Disease Patients in a Multicenter Observational Study.

BACKGROUND: Postural instability and gait difficulties are key symptoms of Parkinson's disease (PD),...

Automated Imaging Differentiation for Parkinsonism.

IMPORTANCE: Magnetic resonance imaging (MRI) paired with appropriate disease-specific machine learni...

Machine learning reveals connections between preclinical type 2 diabetes subtypes and brain health.

Previous research has established type 2 diabetes mellitus as a significant risk factor for various ...

Analysis of Two Neuroanatomical Subtypes of Parkinson's Disease and Their Motor Progression Based on Semi-Supervised Machine Learning.

BACKGROUND: The high heterogeneity of Parkinson's disease (PD) hinders personalized interventions. B...

Identification of CXCR4 inhibitory activity in natural compounds using cheminformatics-guided machine learning algorithms.

Neurodegenerative disorders are characterised by progressive damage to neurons that leads to cogniti...

Gray and white matter alterations in Obsessive-Compulsive Personality Disorder: a data fusion machine learning approach.

INTRODUCTION: Obsessive-Compulsive Personality Disorder (OCPD) is a complex mental condition marked ...

Identification of biomarkers associated with inflammatory response in Parkinson's disease by bioinformatics and machine learning.

Parkinson's disease (PD) is a common and debilitating neurodegenerative disorder. The inflammatory r...

Artificial intelligence based advancements in nanomedicine for brain disorder management: an updated narrative review.

Nanomedicines are nanoscale, biocompatible materials that offer promising alternatives to convention...

Research hotspots and future trends of insomnia in Parkinson's disease: a bibliometric and visualization analysis from 1973 to 2024.

UNLABELLED: Despite the growing body of research on Parkinson's disease (PD) and insomnia, comprehe...

Amphetamine use and Parkinson's disease: integration of artificial intelligence prediction, clinical corroboration, and mechanism of action analyses.

Parkinson's disease (PD) is an increasingly prevalent neurologic condition for which symptomatic, bu...

Deep Learning-Based Prediction of Freezing of Gait in Parkinson's Disease With the Ensemble Channel Selection Approach.

PURPOSE: A debilitating and poorly understood symptom of Parkinson's disease (PD) is freezing of gai...

Uncovering Important Diagnostic Features for Alzheimer's, Parkinson's and Other Dementias Using Interpretable Association Mining Methods.

Alzheimer's Disease and Related Dementias (ADRD) afflict almost 7 million people in the USA alone. T...

m6A-related genes and their role in Parkinson's disease: Insights from machine learning and consensus clustering.

Parkinson disease (PD) is a chronic neurological disorder primarily characterized by a deficiency of...

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