Neurology

Parkinson's Disease

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

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Cognitive signature of brain FDG PET based on deep learning: domain transfer from Alzheimer's disease to Parkinson's disease.

PURPOSE: Although functional brain imaging has been used for the early and objective assessment of c...

A machine learning algorithm successfully screens for Parkinson's in web users.

OBJECTIVE: To develop, apply, and evaluate, a novel web-based classifier for screening for Parkinson...

Automated Parkinson's disease recognition based on statistical pooling method using acoustic features.

Parkinson's disease is one of the mostly seen neurological disease. It affects to nervous system and...

Improved detection of Parkinsonian resting tremor with feature engineering and Kalman filtering.

OBJECTIVE: Accurate and reliable detection of tremor onset in Parkinson's disease (PD) is critical t...

Quantitative susceptibility mapping based hybrid feature extraction for diagnosis of Parkinson's disease.

Parkinson's disease is the second most common neurodegenerative disease in the elderly after Alzheim...

Machine-learning-derived rules set excludes risk of Parkinson's disease in patients with olfactory or gustatory symptoms with high accuracy.

BACKGROUND: Chemosensory loss is a symptom of Parkinson's disease starting already at preclinical st...

Hash Transformation and Machine Learning-Based Decision-Making Classifier Improved the Accuracy Rate of Automated Parkinson's Disease Screening.

Digitalized hand-drawn pattern is a noninvasive and reproducible assistive manner to obtain hand act...

Online identification of functional regions in deep brain stimulation based on an unsupervised random forest with feature selection.

OBJECTIVE: The identification of functional regions, in particular the subthalamic nucleus, through ...

Investigating Risk Factors and Predicting Complications in Deep Brain Stimulation Surgery with Machine Learning Algorithms.

BACKGROUND: Deep brain stimulation (DBS) surgery is an option for patients experiencing medically re...

A Dual-Modal Attention-Enhanced Deep Learning Network for Quantification of Parkinson's Disease Characteristics.

It is well known that most patients with Parkinson's disease (PD) have different degree of movement ...

Bag of Samplings for computer-assisted Parkinson's disease diagnosis based on Recurrent Neural Networks.

Parkinson's Disease (PD) is a clinical syndrome that affects millions of people worldwide. Although ...

Multilevel Features for Sensor-Based Assessment of Motor Fluctuation in Parkinson's Disease Subjects.

Motor fluctuations are a frequent complication in patients with Parkinson's disease (PD) where the r...

Phasic dopamine release identification using convolutional neural network.

Dopamine has a major behavioral impact related to drug dependence, learning and memory functions, as...

A soft continuum robot, with a large variable-stiffness range, based on jamming.

Inspired by the physiological structure of the hand capable of realizing the continuous change in fi...

Quantification of Motor Function in Huntington Disease Patients Using Wearable Sensor Devices.

Previous studies have demonstrated the feasibility and promise of wearable sensors as objective meas...

Development and validation of the automated imaging differentiation in parkinsonism (AID-P): a multicentre machine learning study.

BACKGROUND: Development of valid, non-invasive biomarkers for parkinsonian syndromes is crucially ne...

Development and Validation of the Automated Imaging Differentiation in Parkinsonism (AID-P): A Multi-Site Machine Learning Study.

BACKGROUND: There is a critical need to develop valid, non-invasive biomarkers for Parkinsonian synd...

Clinical effects of robot-assisted gait training and treadmill training for Parkinson's disease. A randomized controlled trial.

BACKGROUND: Although gait disorders strongly contribute to perceived disability in people with Parki...

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