AIMC Topic: Parkinson Disease

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Machine learning-based stratification of mild cognitive impairment in Parkinson's disease: a multicenter cross-sectional analysis.

BMC medical informatics and decision making
BACKGROUND: Cognitive impairment is a prominent non-motor manifestation of Parkinson's disease (PD) and is associated with reduced quality of life, increased mortality, and higher healthcare utilization. We aimed to develop and externally validate a ...

Explainable machine learning algorithm predicting working memory performance in Parkinson's disease using task-fMRI.

Journal of neurology
BACKGROUND: Parkinson's disease (PD) is a neurodegenerative disorder that affects both motor and cognitive functions, particularly working memory (WM). Machine learning offers an advantage for decoding complex brain activity patterns, but its applica...

A Multimodal Convolutional Neural Network Model for Parkinson's Disease Diagnosis Based on Fused Handwriting Dynamics Signals.

Journal of medical systems
Parkinson's disease (PD) is a prevalent and complex neurodegenerative disorder, with early diagnosis playing a critical role in timely treatment and management. Handwriting dynamics has emerged as a promising biomarker for early detection of PD, yet ...

Automatic differentiation of voluntary and tremulous motion using ensemble empirical mode decomposition and convolutional Bi-directional LSTM.

Scientific reports
To develop applications for assisting Parkinson's disease (PD) patients, extracting Parkinsonian tremors from the raw signal is crucial; however, conventional methods such as filtering require a preset frequency range, and a poorly set frequency rang...

Multi-modal deep learning framework for early detection of Parkinson's disease using neurological and physiological data for high-fidelity diagnosis.

Scientific reports
Parkinson's disease (PD) is a progressive neurodegenerative disorder that remained challenging for proper diagnosis in its early stages due to its heterogeneous symptom presentation and overlapping clinical features. Consequently, there is no consens...

Enhanced EfficientNet-Extended Multimodal Parkinson's disease classification with Hybrid Particle Swarm and Grey Wolf Optimizer.

Scientific reports
Parkinson's disease (PD) is a chronic neurodegenerative disorder characterized by progressive loss of dopaminergic neurons in substantia nigra, resulting in both motor impairments and cognitive decline. Traditional PD classification methods are exper...

Micro- and nanoscale biosensing technologies for early diagnosis of Parkinson's disease.

Mikrochimica acta
Parkinson's disease (PD), the second most prevalent neurodegenerative disorder, remains challenging to diagnose at its earliest stages due to the absence of definitive biomarkers and overlapping clinical features with other synucleinopathies, thereby...

Liquiritin in Chaihu-shugan-san alleviates Parkinson's Disease via PPARα-mediated inhibition of SCD1/FADS2-dependent Ferroptosis.

Phytomedicine : international journal of phytotherapy and phytopharmacology
BACKGROUND: Parkinson's disease (PD) is a progressive neurodegenerative disorder with increasing global prevalence. Chaihu-shugan-san (CSS) is a Chinese medicine compound with reported neuroprotective properties. However, the precise bioactive consti...

Differential modulation of movement speed with state-dependent deep brain stimulation in Parkinson's disease.

Science advances
Subthalamic deep brain stimulation (STN-DBS) provides unprecedented spatiotemporal precision for the treatment of Parkinson's disease (PD), allowing for direct real-time state-specific adjustments. Inspired by findings from optogenetic stimulation in...

Syllable-based speech characteristics as potential biomarker for differential diagnosis of Parkinson's disease, multiple system atrophy, and cerebellar ataxia.

Journal of neurology
Speech disorders differ between Parkinson's disease (PD) and multiple system atrophy (MSA), but studies focusing on group differences based on syllables or including cerebellar ataxia (CA) are lacking until now. This cross-sectional study aimed to an...