Neurology

Parkinson's Disease

Latest AI and machine learning research in parkinson's disease for healthcare professionals.

7,179 articles
Stay Ahead - Weekly Parkinson's Disease research updates
Subscribe
Browse Categories
Showing 1241-1260 of 7,179 articles

Measuring Reliability in Locally-deployed Language Model Dysarthric Speech Assessments

Speech is a rich and non-invasive source of clinical information, potentially providing digital biomarkers for neurological disorders such as Parkinson’s disease (PD). Impaired articulation and reduced intelligibility are among the most pervasive PD symptoms, which has motivated research into automated, objective quantification of speech deficits. This study investigated whether metrics derived fr...

Early Detection of Cognitive Decline in Parkinson’s Disease Using Natural Language Processing of Clinical Notes: A Systematic Review and Meta-Analysis Protocol

Cognitive decline affects approximately 40% of Parkinson’s disease (PD) patients within 10 years of diagnosis, progressing to dementia in 80% of patients after 20 years. Early detection of cognitive changes is crucial for timely intervention and care planning. Clinical notes contain rich, longitudinal information about cognitive symptoms that may precede formal diagnosis, yet this unstructured dat...

KG2ML: Integrating Knowledge Graphs and Positive Unlabeled Learning for Identifying Disease-Associated Genes

Biomedical knowledge graphs (KGs), such as the Data Distillery Knowledge Graph (DDKG), capture known relationships among entities (e.g., genes, diseas...

Early Detection of Cognitive Decline in Parkinson’s Disease Using Natural Language Processing of Speech: Protocol for a Systematic Review and Meta-Analysis

Cognitive decline affects up to 80% of Parkinson’s disease (PD) patients, significantly impacting quality of life. Speech changes occur early in PD an...

N2G calibrator: a cross-subject domain adversarial training framework for gait tracking from neural signals in Parkinson’s disease

Adaptive deep brain stimulation has enabled machine learning models to track motor states from neural signals with improved accuracy, aiming to provid...

Quantitative pathology and APOE genotype reveal dementia risk and progression in Lewy body disease

Dementia in Lewy body diseases (LBD) is common and arises through heterogeneous and incompletely understood pathways. Evidence suggests contributions ...

Sex adaptive deep recurrent neural networks for Parkinson’s disease detection using 5-second vertical ground reaction force signals

This study introduces an innovative sex-stratified methodology for the identification of Parkinson’s disease (PD) using vertical ground reaction force...

A Zero-Burden Sleep Foundation Model Built on Cardiorespiratory Signals from 800,000+ Hours of Multi-Ethnic Sleep Recordings

Sleep disorders pose a major global health burden and are associated with a wide range of adverse health outcomes. Polysomnography (PSG) is the gold s...

Integrated Genetic, Molecular, and Wearable Sensor Biomarkers Enable Bayesian Machine Learning-Driven Precision Stratification in Parkinson’s Disease: A Comprehensive Multi-Cohort Validation Study

We present a Bayesian machine learning framework integrating genetic, molecular, and wearable sensor biomarkers for precision medicine in Parkinson’s ...

On Estimating Age and Gender from Parkinson’s Disease Diagnostic-Oriented Recordings Using Wav2Vec 2.0

Can self-supervised speech foundation models (SFMs) be used for automatic patient metadata extraction, even when no prior demographic information is a...

Using Explainable AI to Identify Disease-Relevant and Deep Brain Stimulation Treatment-Sensitive Gait Features in Parkinson’s Disease

Gait impairment is a characteristic motor deficit of Parkinson’s disease (PD) and a critical but insufficiently understood target of deep brain stimul...

Personalized Prediction of Regional Brain Atrophy in Parkinson’s Disease through Longitudinal AI Modeling

Parkinson’s disease (PD) involves variable patterns of brain atrophy in different motor and cognitive regions that differ across patients in both loca...

Predicting Motor Trajectories and Mapping Progression Subtypes in Parkinson’s Disease via Structure–Function Neural Field Encoding and Multi-View Representation

Parkinson’s disease (PD) is characterized by substantial heterogeneity in progression patterns, posing major challenges for individualized prognosis a...

Brain natural frequencies as physiologically meaningful biomarkers for machine-learning detection of Parkinson’s disease

In this study, we investigated whether individual brain maps of natural frequencies derived from EEG can serve as physiologically meaningful biomarker...

Personalized Data-Driven Robust Machine Learning Models to Differentiate Parkinson’s Disease Patients Using Heterogeneous Risk Factors

Parkinson’s Disease (PD) is the most prevalent neurodegenerative disorder after Alzheimer’s, yet its diagnosis largely relies on subjective clinical a...

Gray and white matter alterations in Obsessive-Compulsive Personality Disorder: a data fusion machine learning approach.

INTRODUCTION: Obsessive-Compulsive Personality Disorder (OCPD) is a complex mental condition marked by excessive perfectionism, orderliness, and rigid...

Jan 1 2025 40438540
Artificial intelligence based advancements in nanomedicine for brain disorder management: an updated narrative review.

Nanomedicines are nanoscale, biocompatible materials that offer promising alternatives to conventional treatment options for brain disorders. The rece...

Jan 1 2025 40432717
Research hotspots and future trends of insomnia in Parkinson's disease: a bibliometric and visualization analysis from 1973 to 2024.

UNLABELLED: Despite the growing body of research on Parkinson's disease (PD) and insomnia, comprehensive analysis of overall research trends remains ...

Jan 1 2025 40416738
Identification of biomarkers associated with inflammatory response in Parkinson's disease by bioinformatics and machine learning.

Parkinson's disease (PD) is a common and debilitating neurodegenerative disorder. The inflammatory response is essential in the pathogenesis and progr...

Jan 1 2025 40435035
Amphetamine use and Parkinson's disease: integration of artificial intelligence prediction, clinical corroboration, and mechanism of action analyses.

Parkinson's disease (PD) is an increasingly prevalent neurologic condition for which symptomatic, but not preventative, treatment is available. Drug r...

Jan 1 2025 40392924
Browse Categories