Parkinson's Disease

Metaheuristic-driven machine learning study for early detection and classification of Parkinson's disease using feature prioritization with pelican optimization algorithm.

Parkinson disease (PD) is a degenerative disorder of the brain and afflicts approximately 6 in 10 people aged 50 years or older. PD patients have motor and speech problems, so regular visits to and monitoring of the patients are hard. It is necessary to detect the presence of PD promptly and accurately, since early treatment will contribute greatly to enhancing patients' lives. As the number of ag...

Deep Learning Assisted Heteroporous Covalent Organic Framework Hydrogels Enable Dual-Mode Tracking and Analysis to Parkinson's Management.

Resting tremor and dopamine dysregulation are closely linked in the pathophysiology of Parkinson's disease (PD), yet detecting their subtle early manifestations remains highly challenging. Herein, a wearable hydrogel (Gel@COF), designed for the concurrent monitoring of dopamine levels and resting tremor to enable early PD detection and intervention, is reported. The Gel@COF is fabricated by encaps...

Remote Assessment of Parkinson Disease Using Deep Learning on Structured Mouse-Trace Data From Suspected Cases: Machine-Learning Pilot Feasibility Study.

BACKGROUND: Parkinson disease (PD) is a pervasive neurodegenerative disorder globally, largely characterized by motor symptoms. Most existing artifici...

Interpretable machine learning for Parkinson's disease diagnosis, staging, and biological mechanism exploration: a multicenter analysis.

OBJECTIVE: To develop and validate an interpretable machine learning model based on multicenter T1-weighted MRI radiomics data for the three-way class...

Gait Analysis for Identifying Normal Cognition, Subjective Cognitive Decline, and Mild Cognitive Impairment in Parkinson Disease: Diagnostic Study.

BACKGROUND: Patients with Parkinson disease (PD) along with subjective cognitive decline (PD-SCD) are considered an intermediate status between those ...

Metabolomic signatures of brain aging: A multimodal and genetic study.

Accelerated brain aging is increasingly recognized as a transdiagnostic risk factor for neuropsychiatric and neurodegenerative disorders, yet its meta...

Multi-strategy investigation identifies amentoflavone as a novel D3R antagonist for Parkinson's disease treatment.

BACKGROUND: Parkinson's disease (PD) still lacks therapies that can simultaneously improve symptoms and slow neurodegenerative progression, making the...

Single station seismic observations enable high resolution localization of tectonic tremor sources using a vision transformer.

Precisely locating tectonic tremor events is essential for understanding subduction zone dynamics. However, the lack of impulsive phase arrivals typic...

A Highly Sensitive, Ultrawide-Range Temperature-Pressure Dual-Mode Sensing Platform for Battery Health and Marine Monitoring.

Dual-mode sensors with ultrahigh sensitivity, wide detection range, linearity, and stable temperature response are highly desirable for monitoring in ...

Machine Learning-Based Identification of Distinct Risk Factors for Moderate vs Severe Proximal Junctional Kyphosis After Adult Spinal Deformity Surgery.

BACKGROUND CONTEXT: Proximal junctional kyphosis (PJK) is a well-recognized complication of adult spinal deformity (ASD) surgery. However, traditional...

A skin-conformal rigid-in-soft array-based imaging system.

Array-based imaging systems offer unparalleled capabilities for mapping complex environments, but their inherent structural rigidity prevents intimate...

Interpretable Machine Learning Model for Individualized Survival Prediction of Multiple System Atrophy.

BACKGROUND: Multiple system atrophy (MSA) is a fatal neurodegenerative disease with highly variable progression and poor prognosis. This study aimed t...

Text-Embedding-Assisted Design of Rigid Molecular Cations for Suppressing Ion Migration in Hybrid Single-Crystal X-ray Detectors.

Hybrid single crystals exhibit remarkable optoelectronic properties that make them highly promising for photovoltaic devices and radiation detectors. ...

A Time-Frequency Decoupled Contrastive Learning Framework for Electroencephalography-Based Parkinson's Disease Diagnosis.

Parkinson's disease (PD), a prototypical neurodegenerative disorder, poses significant challenges for early diagnosis. Motivated by recent advances in...

ActiTect: a generalizable machine learning pipeline for REM sleep behavior disorder screening through standardized actigraphy.

Isolated rapid eye movement sleep behavior disorder (iRBD) is a major prodromal marker of α-synucleinopathies, often preceding the clinical onset of P...

Clinically reported covert cerebrovascular disease and risk of neurological disease: a whole-population cohort of 367 988 people using natural language processing.

BACKGROUND: The relevance of covert cerebrovascular disease (CCD) in practice is uncertain, partly because estimation of risk in whole clinical popula...

What can we learn from eye movements in movement disorders and Parkinson's disease?

PURPOSE: Studies of eye movements have evolved from clinical phenomenology to a probe of neural circuitry, cognition, and behavior offering a powerful...

Machine Learning Aided Kinematic Profiling of Reaching Movements Separates Spinocerebellar Ataxia type 12 and Essential Tremor.

Upper limb postural tremor is common in both Spinocerebellar Ataxia type 12 (SCA12) and Essential Tremor (ET). In the early stages, their clinical pre...

A Machine Learning Approach to Voice-Based Parkinson Disease Screening Using Multiview Spectrogram and Speech Recognition Features: Diagnostic Study.

BACKGROUND: Parkinson disease frequently manifests early vocal impairment, motivating the development of noninvasive and scalable digital screening to...

Identifing two distinct cortical progression subtypes of Parkinson's disease through multimodal neuroimaging.

PURPOSE: To investigate whether distinct patterns of cortical involvement exist in Parkinson's disease (PD) and to characterize their potential progre...