Neurology

Parkinson's Disease

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

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Multi-View Graph Convolutional Network and Its Applications on Neuroimage Analysis for Parkinson's Disease.

Parkinson's Disease (PD) is one of the most prevalent neurodegenerative diseases that affects tens o...

Machine learning studies on major brain diseases: 5-year trends of 2014-2018.

In the recent 5 years (2014-2018), there has been growing interest in the use of machine learning (M...

Versatility of fuzzy logic in chronic diseases: A review.

The review aims at providing current state of evidence in the field of medicine with fuzzy logic for...

Wearable sensors for Parkinson's disease: which data are worth collecting for training symptom detection models.

Machine learning algorithms that use data streams captured from soft wearable sensors have the poten...

A machine-learning approach to volitional control of a closed-loop deep brain stimulation system.

OBJECTIVE: Deep brain stimulation (DBS) is a well-established treatment for essential tremor, but ma...

Multi-Source Ensemble Learning for the Remote Prediction of Parkinson's Disease in the Presence of Source-Wise Missing Data.

As the collection of mobile health data becomes pervasive, missing data can make large portions of d...

Self-selected speed gait training in Parkinson's disease: robot-assisted gait training with virtual reality versus gait training on the ground.

BACKGROUND: Parkinson's disease (PD) is a neurodegenerative disorder causing progressive gait disabi...

Electroencephalography-based machine learning for cognitive profiling in Parkinson's disease: Preliminary results.

BACKGROUND: Cognitive symptoms are common in patients with Parkinson's disease. Characterization of ...

Roles for globus pallidus externa revealed in a computational model of action selection in the basal ganglia.

The basal ganglia are considered vital to action selection - a hypothesis supported by several biolo...

A review on microelectrode recording selection of features for machine learning in deep brain stimulation surgery for Parkinson's disease.

OBJECTIVE: This study seeks to systematically review the selection of features and algorithms for ma...

The Combined Use of Transcranial Direct Current Stimulation and Robotic Therapy for the Upper Limb.

Neurologic disorders such as stroke and cerebral palsy are leading causes of long-term disability an...

Implementation of deep neural networks to count dopamine neurons in substantia nigra.

Unbiased estimates of neuron numbers within substantia nigra are crucial for experimental Parkinson'...

Parkinson's Disease Diagnosis via Joint Learning From Multiple Modalities and Relations.

Parkinson's disease (PD) is a neurodegenerative progressive disease that mainly affects the motor sy...

A deep convolutional neural network approach for astrocyte detection.

Astrocytes are involved in various brain pathologies including trauma, stroke, neurodegenerative dis...

Bio-inspired upper limb soft exoskeleton to reduce stroke-induced complications.

Stroke has become the leading cause of disability and the second-leading cause of mortality worldwid...

Multimodal Assessment of Parkinson's Disease: A Deep Learning Approach.

Parkinson's disease is a neurodegenerative disorder characterized by a variety of motor symptoms. Pa...

FESAEI: a fuzzy rule-based expert system for the assessment of environmental impacts : A fuzzy logic approach to impact assessment.

Currently, the method mostly used by practitioners of environmental impact assessment (EIA) is the "...

Structural neuroimaging as clinical predictor: A review of machine learning applications.

In this paper, we provide an extensive overview of machine learning techniques applied to structural...

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