Neurology

Parkinson's Disease

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

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Activity-aware essential tremor evaluation using deep learning method based on acceleration data.

BACKGROUND: Essential tremor (ET), one of the most common neurological disorders is typically evalua...

Convolutional Neural Networks for Neuroimaging in Parkinson's Disease: Is Preprocessing Needed?

Spatial and intensity normalizations are nowadays a prerequisite for neuroimaging analysis. Influenc...

An Intelligent Parkinson's Disease Diagnostic System Based on a Chaotic Bacterial Foraging Optimization Enhanced Fuzzy KNN Approach.

Parkinson's disease (PD) is a common neurodegenerative disease, which has attracted more and more at...

String Grammar Unsupervised Possibilistic Fuzzy C-Medians for Gait Pattern Classification in Patients with Neurodegenerative Diseases.

Neurodegenerative diseases that affect serious gait abnormalities include Parkinson's disease (PD), ...

Effect of Health and Training on Ultrasensitive Cardiac Troponin in Marathon Runners.

PURPOSE: Cardiac troponin (cTn) is the gold standard biomarker for assessing cardiac damage. Previou...

Model-based and Model-free Machine Learning Techniques for Diagnostic Prediction and Classification of Clinical Outcomes in Parkinson's Disease.

In this study, we apply a multidisciplinary approach to investigate falls in PD patients using clini...

Automated assessment of levodopa-induced dyskinesia: Evaluating the responsiveness of video-based features.

INTRODUCTION: Technological solutions for quantifying Parkinson's disease (PD) symptoms may provide ...

Handwritten dynamics assessment through convolutional neural networks: An application to Parkinson's disease identification.

BACKGROUND AND OBJECTIVE: Parkinson's disease (PD) is considered a degenerative disorder that affect...

Thalamocortical dysrhythmia detected by machine learning.

Thalamocortical dysrhythmia (TCD) is a model proposed to explain divergent neurological disorders. I...

Electroencephalographic derived network differences in Lewy body dementia compared to Alzheimer's disease patients.

Dementia with Lewy bodies (DLB) and Alzheimer's disease (AD) require differential management despite...

Rest tremor quantification based on fuzzy inference systems and wearable sensors.

BACKGROUND: Currently the most consistent, widely accepted and detailed instrument to rate Parkinson...

Using echo state networks for classification: A case study in Parkinson's disease diagnosis.

Despite having notable advantages over established machine learning methods for time series analysis...

Improving the Accuracy of Simultaneously Reconstructed Activity and Attenuation Maps Using Deep Learning.

Simultaneous reconstruction of activity and attenuation using the maximum-likelihood reconstruction ...

Wrist sensor-based tremor severity quantification in Parkinson's disease using convolutional neural network.

Tremor is a commonly observed symptom in patients of Parkinson's disease (PD), and accurate measurem...

Motor and psychosocial impact of robot-assisted gait training in a real-world rehabilitation setting: A pilot study.

In the last decade robotic devices have been applied in rehabilitation to overcome walking disabilit...

Evolutionary Wavelet Neural Network ensembles for breast cancer and Parkinson's disease prediction.

Wavelet Neural Networks are a combination of neural networks and wavelets and have been mostly used ...

Characterization of the stimulus waveforms generated by implantable pulse generators for deep brain stimulation.

OBJECTIVE: To determine the circuit elements required to theoretically describe the stimulus wavefor...

Predicting the Effect of Single and Multiple Mutations on Protein Structural Stability.

Predicting how a point mutation alters a protein's stability can guide pharmaceutical drug design in...

Semi-Supervised Discriminative Classification Robust to Sample-Outliers and Feature-Noises.

Discriminative methods commonly produce models with relatively good generalization abilities. Howeve...

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