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Parkinson Disease

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Identification of potential genomic biomarkers for Parkinson's disease using data pooling of gene expression microarrays.

Biomarkers in medicine
In this study, we aimed to identify potential diagnostic biomarkers Parkinson's disease (PD) by exploring microarray gene expression data of PD patients. Differentially expressed genes associated with PD were screened from the GSE99039 dataset usin...

Computational medication regimen for Parkinson's disease using reinforcement learning.

Scientific reports
Our objective is to derive a sequential decision-making rule on the combination of medications to minimize motor symptoms using reinforcement learning (RL). Using an observational longitudinal cohort of Parkinson's disease patients, the Parkinson's P...

Leveraging deep learning to control neural oscillators.

Biological cybernetics
Modulation of the firing times of neural oscillators has long been an important control objective, with applications including Parkinson's disease, Tourette's syndrome, epilepsy, and learning. One common goal for such modulation is desynchronization,...

Effects of robot-assisted gait training on postural instability in Parkinson's disease: a systematic review.

European journal of physical and rehabilitation medicine
INTRODUCTION: Postural instability is a cardinal feature of Parkinson's disease, together with rest tremor, rigidity and bradykinesia. It is a highly disabling symptom that becomes increasingly common with disease progression and represents a major s...

Ensemble deep model for continuous estimation of Unified Parkinson's Disease Rating Scale III.

Biomedical engineering online
BACKGROUND: Unified Parkinson Disease Rating Scale-part III (UPDRS III) is part of the standard clinical examination performed to track the severity of Parkinson's disease (PD) motor complications. Wearable technologies could be used to reduce the ne...

Time-frequency time-space LSTM for robust classification of physiological signals.

Scientific reports
Automated analysis of physiological time series is utilized for many clinical applications in medicine and life sciences. Long short-term memory (LSTM) is a deep recurrent neural network architecture used for classification of time-series data. Here ...

Discovery of novel dual adenosine A1/A2A receptor antagonists using deep learning, pharmacophore modeling and molecular docking.

PLoS computational biology
Adenosine receptors (ARs) have been demonstrated to be potential therapeutic targets against Parkinson's disease (PD). In the present study, we describe a multistage virtual screening approach that identifies dual adenosine A1 and A2A receptor antago...

Interaction of Indirect and Hyperdirect Pathways on Synchrony and Tremor-Related Oscillation in the Basal Ganglia.

Neural plasticity
Low-frequency oscillatory activity (3-9 Hz) and increased synchrony in the basal ganglia (BG) are recognized to be crucial for Parkinsonian tremor. However, the dynamical mechanism underlying the tremor-related oscillations still remains unknown. In ...

Predicting Parkinson's disease trajectory using clinical and neuroimaging baseline measures.

Parkinsonism & related disorders
INTRODUCTION: Predictive biomarkers of Parkinson's Disease progression are needed to expedite neuroprotective treatment development and facilitate prognoses for patients. This work uses measures derived from resting-state functional magnetic resonanc...