Neurology

Parkinson's Disease

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

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Showing 64-84 of 6,137 articles
A New Insight in Cellular and Molecular Signaling Regulation for Neural Differentiation Program.

Numerous neurological conditions impact the brain, spinal cord, and nerves, including neurodegenerat...

Subthalamic nucleus or globus pallidus internus deep brain stimulation for the treatment of parkinson's disease: An artificial intelligence approach.

BACKGROUND: Generative artificial intelligence (AI) in deep brain stimulation (DBS) is currently unv...

Multi-Scale Temporal Analysis with a Dual-Branch Attention Network for Interpretable Gait-Based Classification of Neurodegenerative Diseases.

The accurate diagnosis of neurodegenerative diseases (NDDs), such as Amyotrophic Lateral Sclerosis (...

Decoding Parkinson's Diagnosis: An OCT-Based Explainable AI with SHAP/LIME Transparency from the Persian Cohort Study.

BACKGROUND: Parkinson's disease (PD) diagnosis remains challenging due to subjective clinical assess...

FedOcw: optimized federated learning for cross-lingual speech-based Parkinson's disease detection.

Accurate detection of Parkinson's disease (PD) through speech analysis holds great promise for early...

Clinical correlates of data-driven subtypes of deep gray matter atrophy and dopamine availability in early Parkinson's disease.

Recent machine-learning techniques may be useful to identify subtypes with distinct spatial patterns...

POC-CSP: a novel parameterised and orthogonally-constrained neural network layer for learning common spatial patterns (CSP) in EEG signals.

. Common spatial patterns (CSPs) has been established as a powerful feature extraction method in EEG...

Deep learning enhanced deciphering of brain activity maps for discovery of therapeutics for brain disorders.

This study presents an artificial intelligence enhanced screening platform, DeepBAM, which enables ...

Thalamic neural activity and epileptic network analysis using stereoelectroencephalography: a prospective study protocol.

INTRODUCTION: Epilepsy is a prevalent chronic neurological disorder, with approximately one-third of...

Deep-learning-based Partial Volume Correction in 99mTc-TRODAT-1 SPECT for Parkinson's Disease: A Preliminary Study on Clinical Translation.

Tc-TRODAT-1 SPECT is effective for the early detection of Parkinson's disease (PD). However, SPECT i...

O-GEST: Overground gait events detector using b-spline-based geometric models for marker-based and markerless analysis.

Accurate gait events detection is imperative for reliable assessment of normal and pathological gait...

Using machine learning to identify Parkinson's disease severity subtypes with multimodal data.

BACKGROUND: Classifying and predicting Parkinson's disease (PD) is challenging because of its divers...

In vivo and in silico models of Drosophila for Parkinson's disease.

The fruit fly Drosophila melanogaster has emerged as an important model organism to shed light on ne...

Prediction of 123I-FP-CIT SPECT Results from First Acquired Projections Using Artificial Intelligence.

123I-FP-CIT dopamine transporter imaging is commonly used for the diagnosis of Parkinsonian syndrom...

Microglia-drive IRF8 upregulates complement pathway in Parkinson's disease.

Parkinson's disease (PD) is a widespread degenerative disorder of the central nervous system. The gr...

Estimating motor symptom presence and severity in Parkinson's disease from wrist accelerometer time series using ROCKET and InceptionTime.

Parkinson's disease (PD) is a neurodegenerative condition characterized by frequently changing motor...

Personalized medication recommendations for Parkinson's disease patients using gated recurrent units and SHAP interpretability.

Managing Parkinson's disease (PD) through medication can be challenging due to varying symptoms and ...

Distinct brain atrophy progression subtypes underlie phenoconversion in isolated REM sleep behaviour disorder.

BACKGROUND: Synucleinopathies include a spectrum of disorders varying in features and severity, incl...

Decoding dynamic brain networks in Parkinson's disease with temporal attention.

Detecting brief, clinically meaningful changes in brain activity is crucial for understanding neurol...

An Artificial Intelligence Olfactory-Based Diagnostic Model for Parkinson's Disease Using Volatile Organic Compounds from Ear Canal Secretions.

Parkinson's Disease (PD), a frequently diagnosed neurodegenerative condition, poses a major global c...

Detecting Tardive Dyskinesia Using Video-Based Artificial Intelligence.

Tardive dyskinesia (TD) is a late-onset adverse effect of dopamine receptor-blocking medications, c...

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