Neurology

Parkinson's Disease

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

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A new network structure for Parkinson's handwriting image recognition.

Parkinson's disease (PD) remains a condition without a cure, though its early manifestations can be ...

May 2025 40306883
Neurophysiologically Realistic Environment for Comparing Adaptive Deep Brain Stimulation Algorithms in Parkinson Disease

Adaptive deep brain stimulation (aDBS) has emerged as a promising treatment for Parkinson disease ...

Edge-boosted graph learning for functional brain connectivity analysis

Predicting disease states from functional brain connectivity is critical for the early diagnosis o...

MAAM: A Lightweight Multi-Agent Aggregation Module for Efficient Image Classification Based on the MindSpore Framework

The demand for lightweight models in image classification tasks under resource-constrained environ...

Beyond Feature Importance: Feature Interactions in Predicting Post-Stroke Rigidity with Graph Explainable AI

This study addresses the challenge of predicting post-stroke rigidity by emphasizing feature inter...

Machine learning reveals connections between preclinical type 2 diabetes subtypes and brain health.

Previous research has established type 2 diabetes mellitus as a significant risk factor for various ...

Apr 2025 39932872
GAITGen: Disentangled Motion-Pathology Impaired Gait Generative Model -- Bringing Motion Generation to the Clinical Domain

Gait analysis is crucial for the diagnosis and monitoring of movement disorders like Parkinson's D...

Adaptive Wavelet Filters as Practical Texture Feature Amplifiers for Parkinson's Disease Screening in OCT

Parkinson's disease (PD) is a prevalent neurodegenerative disorder globally. The eye's retina is a...

Sensory-driven microinterventions for improved health and wellbeing

The five senses are gateways to our wellbeing and their decline is considered a significant public...

Oscillatory Signatures of Parkinson's Disease: Central and Parietal EEG Alterations Across Multiple Frequency Bands

This study investigates EEG as a potential early biomarker by applying deep learning techniques to...

Bilingual Dual-Head Deep Model for Parkinson's Disease Detection from Speech

This work aims to tackle the Parkinson's disease (PD) detection problem from the speech signal in ...

SIRE: SE(3) Intrinsic Rigidity Embeddings

Motion serves as a powerful cue for scene perception and understanding by separating independently...

AI-Enabled Conversational Journaling for Advancing Parkinson's Disease Symptom Tracking

Journaling plays a crucial role in managing chronic conditions by allowing patients to document sy...

The order in speech disorder: a scoping review of state of the art machine learning methods for clinical speech classification

Background:Speech patterns have emerged as potential diagnostic markers for conditions with varyin...

A digital eye-fixation biomarker using a deep anomaly scheme to classify Parkisonian patterns

Oculomotor alterations constitute a promising biomarker to detect and characterize Parkinson's dis...

Predictability of temporal network dynamics in normal ageing and brain pathology

Spontaneous brain activity generically displays transient spatiotemporal coherent structures, whic...

Radar Network for Gait Monitoring: Technology and Validation

In recent years, radar-based devices have emerged as an alternative approach for gait monitoring. ...

Artificial intelligence-enabled detection and assessment of Parkinson's disease using multimodal data: A survey

The rapid emergence of highly adaptable and reusable artificial intelligence (AI) models is set to...

Lifespan tree of brain anatomy: diagnostic values for motor and cognitive neurodegenerative diseases

The differential diagnosis of neurodegenerative diseases, characterized by overlapping symptoms, m...

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