AIMC Topic: Parkinson Disease

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Parkinson's disease: deep learning with a parameter-weighted structural connectome matrix for diagnosis and neural circuit disorder investigation.

Neuroradiology Jan 22, 2021
PURPOSE: To investigate whether Parkinson's disease (PD) can be differentiated from healthy controls and to identify neural circuit disorders in PD by applying a deep learning technique to parameter-weighted and number of streamlines (NOS)-based stru...
Humans Prospective Studies Deep Learning Parkinson Disease Connectome Diffusion Tensor Imaging
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Clinical value of machine learning-based interpretation of I-123 FP-CIT scans to detect Parkinson's disease: a two-center study.

Annals of nuclear medicine Jan 20, 2021
PURPOSE: Our aim was to develop and validate a machine learning (ML)-based approach for interpretation of I-123 FP-CIT SPECT scans to discriminate Parkinson's disease (PD) from non-PD and to determine its generalizability and clinical value in two ce...
Male Middle Aged Support Vector Machine Parkinson Disease Image Interpretation, Computer-Assisted Machine Learning Tomography, Emission-Computed, Single-Photon Retrospective Studies Tropanes Female Aged Humans
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Schizotypy in Parkinson's disease predicts dopamine-associated psychosis.

Scientific reports Jan 12, 2021
Psychosis is the most common neuropsychiatric side-effect of dopaminergic therapy in Parkinson's disease (PD). It is still unknown which factors determine individual proneness to psychotic symptoms. Schizotypy is a multifaceted personality trait rela...
Cross-Sectional Studies Male Middle Aged Case-Control Studies Psychotic Disorders Humans Dopamine Machine Learning Hallucinations Surveys and Questionnaires Female Schizotypal Personality Disorder ROC Curve Emotions Parkinson Disease
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Learning fine-grained estimation of physiological states from coarse-grained labels by distribution restoration.

Scientific reports Dec 15, 2020
Due to its importance in clinical science, the estimation of physiological states (e.g., the severity of pathological tremor) has aroused growing interest in machine learning community. While the physiological state is a continuous variable, its cont...
Neural Networks, Computer Machine Learning Algorithms Severity of Illness Index Parkinson Disease Blood Pressure Tremor Humans
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Unobtrusive detection of Parkinson's disease from multi-modal and in-the-wild sensor data using deep learning techniques.

Scientific reports Dec 7, 2020
Parkinson's Disease (PD) is the second most common neurodegenerative disorder, affecting more than 1% of the population above 60 years old with both motor and non-motor symptoms of escalating severity as it progresses. Since it cannot be cured, treat...
Sensitivity and Specificity Male Middle Aged Quality of Life Humans Female Aged Deep Learning ROC Curve Parkinson Disease
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An easy-to-use deep-learning model for highly accurate diagnosis of Parkinson's disease using SPECT images.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society Nov 24, 2020
Accurate diagnosis of Parkinson's Disease (PD) at its early stages remains a challenge for modern clinicians. In this study, we utilize a convolutional neural network (CNN) approach to address this problem. In particular, we develop a CNN-based netwo...
Humans Neural Networks, Computer Deep Learning Parkinson Disease Tomography, Emission-Computed, Single-Photon
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Using machine learning-based analytics of daily activities to identify modifiable risk factors for falling in Parkinson's disease.

Parkinsonism & related disorders Nov 19, 2020
BACKGROUND: Although risk factors that lead to falling in Parkinson's disease (PD) have been previously studied, the established predictors are mostly non-modifiable. A novel method for fall risk assessment may provide more insight into preventable h...
Supervised Machine Learning Activities of Daily Living Antiparkinson Agents Age Factors Parkinson Disease Postural Balance Aged Male Middle Aged Risk Assessment Severity of Illness Index Humans Accidental Falls Prognosis Models, Theoretical Female Risk Factors
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Machine learning discriminates a movement disorder in a zebrafish model of Parkinson's disease.

Disease models & mechanisms Oct 16, 2020
Animal models of human disease provide an system that can reveal molecular mechanisms by which mutations cause pathology, and, moreover, have the potential to provide a valuable tool for drug development. Here, we have developed a zebrafish model of...
Movement Dopaminergic Neurons Movement Disorders Gene Targeting Protein Deglycase DJ-1 Mutation Alleles Zebrafish Base Sequence Machine Learning Gene Expression Profiling Algorithms Disease Models, Animal Brain Parkinson Disease Animals
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Parkinson's Disease Tremor Detection in the Wild Using Wearable Accelerometers.

Sensors (Basel, Switzerland) Oct 14, 2020
Continuous in-home monitoring of Parkinson's Disease (PD) symptoms might allow improvements in assessment of disease progression and treatment effects. As a first step towards this goal, we evaluate the feasibility of a wrist-worn wearable accelerome...
Wearable Electronic Devices Humans Parkinson Disease Neural Networks, Computer Accelerometry Deep Learning Tremor
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Reconstructing lost BOLD signal in individual participants using deep machine learning.

Nature communications Oct 7, 2020
Signal loss in blood oxygen level-dependent (BOLD) functional neuroimaging is common and can lead to misinterpretation of findings. Here, we reconstructed compromised fMRI signal using deep machine learning. We trained a model to learn principles gov...
Parkinson Disease Brain Mapping Oxygen Deep Brain Stimulation Image Processing, Computer-Assisted Magnetic Resonance Imaging Humans Models, Neurological Healthy Volunteers Female Datasets as Topic Young Adult Adult Cerebral Cortex Male Deep Learning Adolescent
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