Neurology

Parkinson's Disease

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

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Parkinson's image detection and classification based on deep learning.

OBJECTIVE: There are two major issues in the MRI image diagnosis task for Parkinson's disease. First...

Accelerating multipool CEST MRI of Parkinson's disease using deep learning-based Z-spectral compressed sensing.

PURPOSE: To develop a deep learning-based approach to reduce the scan time of multipool CEST MRI for...

Adaptive node feature extraction in graph-based neural networks for brain diseases diagnosis using self-supervised learning.

Electroencephalography (EEG) has demonstrated significant value in diagnosing brain diseases. In par...

Quantum-level machine learning calculations of Levodopa.

Many drug molecules contain functional groups, resulting in a torsional barrier corresponding to rot...

Hierarchical multi-task deep learning-assisted construction of human gut microbiota reactive oxygen species-scavenging enzymes database.

In the process of oxygen reduction, reactive oxygen species (ROS) are generated as intermediates, in...

Prediction of Freezing of Gait in Parkinson's disease based on multi-channel time-series neural network.

Freezing of Gait (FOG) is a noticeable symptom of Parkinson's disease, like being stuck in place and...

Artificial intelligence in Parkinson's disease: Early detection and diagnostic advancements.

Parkinson's disease (PD) is the second most common neurodegenerative disorder, globally affecting me...

Levodopa-induced dyskinesia in Parkinson's disease: Insights from cross-cohort prognostic analysis using machine learning.

BACKGROUND: Prolonged levodopa treatment in Parkinson's disease (PD) often leads to motor complicati...

A causal counterfactual graph neural network for arising-from-chair abnormality detection in parkinsonians.

The arising-from-chair task assessment is a key aspect of the evaluation of movement disorders in Pa...

Advances in Computational Biology for Diagnosing Neurodegenerative Diseases: A Comprehensive Review.

The numerous and varied forms of neurodegenerative illnesses provide a considerable challenge to con...

Generalisation capabilities of machine-learning algorithms for the detection of the subthalamic nucleus in micro-electrode recordings.

PURPOSE: Micro-electrode recordings (MERs) are a key intra-operative modality used during deep brain...

Characterizing Disease Progression in Parkinson's Disease from Videos of the Finger Tapping Test.

INTRODUCTION: Parkinson's disease (PD) is characterized by motor symptoms whose progression is typic...

Assessing gait dysfunction severity in Parkinson's Disease using 2-Stream Spatial-Temporal Neural Network.

Parkinson's Disease (PD), a neurodegenerative disorder, significantly impacts the quality of life fo...

An improved method for diagnosis of Parkinson's disease using deep learning models enhanced with metaheuristic algorithm.

Parkinson's disease (PD) is challenging for clinicians to accurately diagnose in the early stages. Q...

Video-Based Detection of Freezing of Gait in Daily Clinical Practice in Patients With Parkinsonism.

Freezing of gait (FoG) is a prevalent symptom among individuals with Parkinson's disease and related...

3D Printed Magnetic Bionic Robot Inspired by Octopus for Drug Transportation.

The octopus has attracted widespread attention owing to its unique underwater movement and its abili...

Insights into Parkinson's Disease-Related Freezing of Gait Detection and Prediction Approaches: A Meta Analysis.

Parkinson's Disease (PD) is a complex neurodegenerative disorder characterized by a spectrum of moto...

Classification of Parkinson's disease severity using gait stance signals in a spatiotemporal deep learning classifier.

Parkinson's disease (PD) is a degenerative nervous system disorder involving motor disturbances. Mot...

Deep Learning for hand tracking in Parkinson's Disease video-based assessment: Current and future perspectives.

BACKGROUND: Parkinson's Disease (PD) demands early diagnosis and frequent assessment of symptoms. In...

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