AIMC Topic: Parkinson Disease

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

Movement disorders : official journal of the Movement Disorder Society Feb 1, 2022
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.
Humans Deep Learning Substantia Nigra Melanins REM Sleep Behavior Disorder Magnetic Resonance Imaging Parkinson Disease Parkinsonian Disorders
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Metaheuristics with Deep Learning-Enabled Parkinson's Disease Diagnosis and Classification Model.

Journal of healthcare engineering Jan 10, 2022
Parkinson's disease (PD) affects the movement of people, including the differences in writing skill, speech, tremor, and stiffness in muscles. It is significant to detect the PD at the initial stages so that the person can live a peaceful life for a ...
Humans Algorithms Rats Animals Parkinson Disease Deep Learning Walking Speech
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Identification of an early-stage Parkinson's disease neuromarker using event-related potentials, brain network analytics and machine-learning.

PloS one Jan 7, 2022
OBJECTIVE: The purpose of this study is to explore the possibility of developing a biomarker that can discriminate early-stage Parkinson's disease from healthy brain function using electroencephalography (EEG) event-related potentials (ERPs) in combi...
Evoked Potentials Middle Aged Parkinson Disease Electroencephalography Female Humans Aged Machine Learning Male Brain
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Deep learning reveals personalized spatial spectral abnormalities of high delta and low alpha bands in EEG of patients with early Parkinson's disease.

Journal of neural engineering Dec 24, 2021
Parkinson's disease (PD) is one of the most common neurodegenerative diseases, and early diagnosis is crucial to delay disease progression. The diagnosis of early PD has always been a difficult clinical problem due to the lack of reliable biomarkers....
Humans Electroencephalography Neural Networks, Computer Deep Learning Parkinson Disease
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Combination of liquid crystal and deep learning reveals distinct signatures of Parkinson's disease-related wild-type α-synuclein and six pathogenic mutants.

Chemistry, an Asian journal Dec 21, 2021
α-Synuclein is a central player in Parkinson's disease (PD) pathology. Various point mutations in α-synuclein have been identified to alter the protein-phospholipid binding behavior and cause PD. Therefore, exploration of α-synuclein-phospholipid int...
Mutation Liquid Crystals Deep Learning Parkinson Disease alpha-Synuclein Humans
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Data-driven identification of diagnostically useful extrastriatal signal in dopamine transporter SPECT using explainable AI.

Scientific reports Nov 25, 2021
This study used explainable artificial intelligence for data-driven identification of extrastriatal brain regions that can contribute to the interpretation of dopamine transporter SPECT with I-FP-CIT in parkinsonian syndromes. A total of 1306 I-FP-CI...
Tropanes Dopamine Plasma Membrane Transport Proteins Nerve Degeneration Radiopharmaceuticals Brain Humans Image Interpretation, Computer-Assisted Retrospective Studies Neural Networks, Computer Parkinson Disease Tomography, Emission-Computed, Single-Photon Reproducibility of Results Diagnosis, Differential Predictive Value of Tests
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Fully automated deep learning-based localization and segmentation of the locus coeruleus in aging and Parkinson's disease using neuromelanin-sensitive MRI.

International journal of computer assisted radiology and surgery Nov 19, 2021
PURPOSE: Development and performance measurement of a fully automated pipeline that localizes and segments the locus coeruleus in so-called neuromelanin-sensitive magnetic resonance imaging data for the derivation of quantitative biomarkers of neurod...
Image Processing, Computer-Assisted Magnetic Resonance Imaging Parkinson Disease Melanins Locus Coeruleus Humans Deep Learning
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Effect of data leakage in brain MRI classification using 2D convolutional neural networks.

Scientific reports Nov 19, 2021
In recent years, 2D convolutional neural networks (CNNs) have been extensively used to diagnose neurological diseases from magnetic resonance imaging (MRI) data due to their potential to discern subtle and intricate patterns. Despite the high perform...
Neuroimaging Alzheimer Disease Image Interpretation, Computer-Assisted Humans Neural Networks, Computer Brain Middle Aged Aged, 80 and over Magnetic Resonance Imaging Case-Control Studies Female Cross-Sectional Studies Deep Learning Parkinson Disease Male Reproducibility of Results Predictive Value of Tests Aged
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Self-paced learning and privileged information based KRR classification algorithm for diagnosis of Parkinson's disease.

Neuroscience letters Oct 29, 2021
Computer aided diagnosis (CAD) methods for Parkinson's disease (PD) can assist clinicians in diagnosis and treatment. Magnetic resonance imaging (MRI) based CAD methods can help reveal structural changes in brain. Classifier is a key component in CAD...
Magnetic Resonance Imaging Parkinson Disease Image Interpretation, Computer-Assisted Male Humans Machine Learning Middle Aged Neural Networks, Computer Neuroimaging Female Diagnosis, Computer-Assisted Aged
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Application of Deep Learning Models for Automated Identification of Parkinson's Disease: A Review (2011-2021).

Sensors (Basel, Switzerland) Oct 23, 2021
Parkinson's disease (PD) is the second most common neurodegenerative disorder affecting over 6 million people globally. Although there are symptomatic treatments that can increase the survivability of the disease, there are no curative treatments. Th...
Gait Deep Learning Humans Speech Artificial Intelligence Parkinson Disease
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