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Parkinsonian Disorders

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

The Lancet. Digital health
BACKGROUND: There is a critical need to develop valid, non-invasive biomarkers for Parkinsonian syndromes. The current 17-site, international study assesses whether non-invasive diffusion MRI (dMRI) can distinguish between Parkinsonian syndromes.

Automated Imaging Differentiation for Parkinsonism.

JAMA neurology
IMPORTANCE: Magnetic resonance imaging (MRI) paired with appropriate disease-specific machine learning holds promise for the clinical differentiation of Parkinson disease (PD), multiple system atrophy (MSA) parkinsonian variant, and progressive supra...

Decoding the dopamine transporter imaging for the differential diagnosis of parkinsonism using deep learning.

European journal of nuclear medicine and molecular imaging
PURPOSE: This work attempts to decode the discriminative information in dopamine transporter (DAT) imaging using deep learning for the differential diagnosis of parkinsonism.

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.

Multi-View Mouse Social Behaviour Recognition With Deep Graphic Model.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Home-cage social behaviour analysis of mice is an invaluable tool to assess therapeutic efficacy of neurodegenerative diseases. Despite tremendous efforts made within the research community, single-camera video recordings are mainly used for such ana...

Revealing posturographic profile of patients with Parkinsonian syndromes through a novel hypothesis testing framework based on machine learning.

PloS one
Falling in Parkinsonian syndromes (PS) is associated with postural instability and consists a common cause of disability among PS patients. Current posturographic practices record the body's center-of-pressure displacement (statokinesigram) while the...

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

The Lancet. Digital health
BACKGROUND: Development of valid, non-invasive biomarkers for parkinsonian syndromes is crucially needed. We aimed to assess whether non-invasive diffusion-weighted MRI can distinguish between parkinsonian syndromes using an automated imaging approac...

A 3D Deep Residual Convolutional Neural Network for Differential Diagnosis of Parkinsonian Syndromes on F-FDG PET Images.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Idiopathic Parkinsons disease and atypical parkinsonian syndromes have similar symptoms at early disease stages, which makes the early differential diagnosis difficult. Positron emission tomography with F-FDG shows the ability to assess early neurona...