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Parkinson Disease

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Optimization-Based Ensemble Feature Selection Algorithm and Deep Learning Classifier for Parkinson's Disease.

Journal of healthcare engineering
PD (Parkinson's Disease) is a severe malady that is painful and incurable, affecting older human beings. Identifying PD early in a precise manner is critical for the lengthened survival of patients, where DMTs (data mining techniques) and MLTs (machi...

Integrating deep learning and unbiased automated high-content screening to identify complex disease signatures in human fibroblasts.

Nature communications
Drug discovery for diseases such as Parkinson's disease are impeded by the lack of screenable cellular phenotypes. We present an unbiased phenotypic profiling platform that combines automated cell culture, high-content imaging, Cell Painting, and dee...

Identification of Novel Noninvasive Diagnostics Biomarkers in the Parkinson's Diseases and Improving the Disease Classification Using Support Vector Machine.

BioMed research international
BACKGROUND: Parkinson's disease (PD) is a neurological disorder that is marked by the deficit of neurons in the midbrain that changes motor and cognitive function. In the substantia nigra, the selective demise of dopamine-producing neurons was the ma...

Deep learning based diagnosis of Parkinson's Disease using diffusion magnetic resonance imaging.

Brain imaging and behavior
The diagnostic performance of a combined architecture on Parkinson's disease using diffusion tensor imaging was evaluated. A convolutional neural network was trained from multiple parcellated brain regions. A greedy algorithm was proposed to combine ...

Acceptability and Preliminary Results of Technology-Assisted Balance Training in Parkinson's Disease.

International journal of environmental research and public health
(1) Background: Parkinson's Disease (PD) is one of the most common causes of disability among older individuals. The advanced stages of PD are usually characterized by postural instability and, as a consequence, falls. Those are among the main factor...

Resting-state electroencephalography based deep-learning for the detection of Parkinson's disease.

PloS one
Parkinson's disease (PD) is one of the most serious and challenging neurodegenerative disorders to diagnose. Clinical diagnosis on observing motor symptoms is the gold standard, yet by this point nerve cells are degenerated resulting in a lower effic...

Robot-assisted gait training with auditory and visual cues in Parkinson's disease: A randomized controlled trial.

Annals of physical and rehabilitation medicine
BACKGROUND: Robot-assisted gait training (RAGT) may have beneficial effects on Parkinson's disease (PD); however, the evidence to date is inconsistent.

Predicting Motor Responsiveness to Deep Brain Stimulation with Machine Learning.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Deep brain stimulation is a complex movement disorder intervention that requires highly invasive brain surgery. Clinicians struggle to predict how patients will respond to this treatment. To address this problem, we are working toward developing a cl...

Antemortem detection of Parkinson's disease pathology in peripheral biopsies using artificial intelligence.

Acta neuropathologica communications
The diagnosis of Parkinson's disease (PD) is challenging at all stages due to variable symptomatology, comorbidities, and mimicking conditions. Postmortem assessment remains the gold standard for a definitive diagnosis. While it is well recognized th...

Deep Learning-Based Neuromelanin MRI Changes of Isolated REM Sleep Behavior Disorder.

Movement disorders : official journal of the Movement Disorder Society
BACKGROUND: Isolated REM sleep behavior disorder (iRBD) is considered a prodromal stage of parkinsonism. Neurodegenerative changes in the substantia nigra pars compacta (SNc) in parkinsonism can be detected using neuromelanin-sensitive MRI.