Parkinson's Disease

LadderGen: a large-scale generative library of ladder polymers for membrane separations.

Ladder polymers possess exceptional rigidity, microporosity, and thermal stability, yet their exploration as gas separation membranes is hindered by the scarcity of synthetically accessible chemical structures. Here, we introduce LadderGen, a large-scale hypothetical ladder polymer library constructed using template polymerization reactions and advanced generative machine learning (ML) models, exp...

Hierarchical Coarse-to-Fine cGAN for Subtype-Specific Freezing of Gait Signal Generation.

Freezing of gait (FOG), a debilitating symptom of Parkinson's disease, can manifest in three sub-types: shuffling, trembling, and akinesia, with occurrence and frequency varying across patients. While deep learning (DL) models show promise in FOG detection, their robustness and generalization across subtypes are limited by data scarcity and imbalances between FOG/non-FOG classes and among subtypes...

Neuromodulation-induced normalization of cortical metastable dynamics signatures in Parkinson's disease.

Deep brain stimulation (DBS) of the subthalamic nucleus (STN) alleviates motor symptoms in Parkinson's disease (PD), but how it modulates whole-brain ...

Use of Machine Learning to Identify Markers of Risk for Fragile X-Associated Tremor/Ataxia Syndrome: A Preliminary Analysis.

OBJECTIVE: The objective of this study was to examine whether machine learning has the capacity to prospectively identify and predict the emergence of...

Transformation of Parkinson's care through SMART-PD (Self-Management, Remote monitoring and Timely review for Parkinson's Disease): Care pathway mapping with clinical experts.

Purpose of researchSMaRT-PD is a clinical decision support system (CDSS) for the home-based management and care of Parkinson's disease. It utilises re...

MRI-Guided High-Intensity Focused Ultrasound in Movement Disorders: Targeting Pathologic Brain Circuits With Precision Imaging, From the AJR Special Series on Critical Anatomy.

MRI-guided high-intensity focused ultrasound (MRgHIFU) has emerged as an alternative to other neuromodulatory interventions for patients with medicall...

ML-Based Multidomain Speech Biomarkers for Multiclass Parkinson's Severity: An Indian Corpus and Clinically Calibrated Labels.

OBJECTIVE: Speech provides a lightweight window into articulatory and phonatory impairment in Parkinson's Disease (PD), yet clinically reliable severi...

Digital Technology for Sleep Symptoms in Parkinson's Disease: A Scoping Review.

Sleep disturbances are highly prevalent and clinically significant non-motor features of Parkinson's disease (PD). Although in-laboratory polysomnogra...

Alzheimer's and Parkinson's Detection with Video-Based Hybrid Deep Learning from Brain MRI.

Dementia, which refers to disorders related to human memory, significantly affects the human brain, and a person with it can experience certain diffic...

Machine Learning Identifies TRAPPC13/COPS5 as Biomarkers and Vesicle Transport Subtypes in Parkinson's Disease.

BACKGROUND: Parkinson's disease (PD) is a neurodegenerative disorder characterized by neuron loss and abnormal protein trafficking. Dysregulation of v...

Geo-Mamba: Geometry-informed state-space learning of functional brain organization.

Functional magnetic resonance imaging (fMRI) derived functional connectivity (FC) is represented as graphs and as correlation or covariance matrices t...

Classification of fallers in Parkinson's disease through machine learning based feature analysis.

Classification of fallers in Parkinson's disease (PD) is challenging due to the heterogenous motor and non-motor symptoms. We developed a machine lear...

Neuromodulation of the central nervous system for facial pain.

Chronic craniofacial pain can lead to significant morbidity and reduced quality-of-life. Refractory pain subsequently leads to maladaptive changes wit...

Pathology-Anchored Transcranial Sonography: A Cascaded Super-Resolution Deep Learning System for Early-Stage Parkinson's Disease Grading.

Delayed diagnosis of Parkinson's disease (PD) due to undetectable early pathological changes remains a major clinical challenge limiting effective tre...

A graph deep learning method for diagnosis of Parkinson's disease using brain functional connectivity features.

Early and precise identification of Parkinson's disease (PD) is crucial for clinical intervention. Resting-state functional magnetic resonance imaging...

Classification of functional brain patterns elicited by deep brain stimulation of the subthalamic nucleus in Parkinson's disease.

Despite the remarkable success of deep brain stimulation (DBS) in alleviating Parkinson's disease (PD) symptoms, complexities arising from inherent in...

Leveraging machine learning to predict Parkinson's disease using pre-symptomatic proteomics data.

In Parkinson's disease, non-motor symptoms precede the characteristic motor manifestations by up to 20 years. However, predicting the disease risk rem...

Quantitative susceptibility mapping and MRS-based multimodal machine learning for early Parkinson's disease classification.

Parkinson's disease (PD) is a complex, progressive neurodegenerative disorder characterized by high heterogeneity and diagnostic challenges in its ear...

Focused ultrasound thalamotomy improves voice tremor in essential tremor: objective insight from artificial intelligence.

An enhanced framework for Parkinson's disease severity prediction using improved optimization in multi-scale TCN.

RESEARCH BACKGROUND: Parkinson's Disease (PD) requires accurate severity prediction models for enabling efficient treatment planning and disease manag...