Neurology

Parkinson's Disease

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

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PIDGN: An explainable multimodal deep learning framework for early prediction of Parkinson's disease.

BACKGROUND: Parkinson's disease (PD), the second most common neurodegenerative disease in the world,...

Automated analysis of spoken language differentiates multiple system atrophy from Parkinson's disease.

BACKGROUND AND OBJECTIVES: Patients with synucleinopathies such as multiple system atrophy (MSA) and...

PADS-Net: GAN-based radiomics using multi-task network of denoising and segmentation for ultrasonic diagnosis of Parkinson disease.

Parkinson disease (PD) is a prevalent neurodegenerative disorder, and its accurate diagnosis is cruc...

Deep learning-based differential gut flora for prediction of Parkinson's.

BACKGROUND: There had been extensive research on the role of the gut microbiota in human health and ...

Real-time isolation of physiological tremor using recursive singular spectrum analysis and random vector functional link for surgical robotics.

Hand-held robotic instruments enhance precision in microsurgery by mitigating physiological tremor i...

DDEvENet: Evidence-based ensemble learning for uncertainty-aware brain parcellation using diffusion MRI.

In this study, we developed an Evidential Ensemble Neural Network based on Deep learning and Diffusi...

Drug repositioning for Parkinson's disease: An emphasis on artificial intelligence approaches.

Parkinson's disease (PD) is one of the most incapacitating neurodegenerative diseases (NDDs). PD is ...

Gait-based Parkinson's disease diagnosis and severity classification using force sensors and machine learning.

A dual-stage model for classifying Parkinson's disease severity, through a detailed analysis of Gait...

Selective diagnostics of Amyotrophic Lateral Sclerosis, Alzheimer's and Parkinson's Diseases with machine learning and miRNA.

The diagnosis of neurological diseases can be expensive, invasive, and inaccurate, as it is often di...

Machine learning for early detection and severity classification in people with Parkinson's disease.

Early detection of Parkinson's disease (PD) and accurate assessment of disease progression are criti...

Deep Learning-Based Ion Channel Kinetics Analysis for Automated Patch Clamp Recording.

The patch clamp technique is a fundamental tool for investigating ion channel dynamics and electroph...

Identifying the NEAT1/miR-26b-5p/S100A2 axis as a regulator in Parkinson's disease based on the ferroptosis-related genes.

OBJECTIVES: Parkinson's disease (PD) is a complex neurodegenerative disease with unclear pathogenesi...

A robust Parkinson's disease detection model based on time-varying synaptic efficacy function in spiking neural network.

Parkinson's disease (PD) is a neurodegenerative disease affecting millions of people around the worl...

Computer model for gait assessments in Parkinson's patients using a fuzzy inference model and inertial sensors.

Patients with Parkinson's disease (PD) in the moderate and severe stages can present several walk al...

Understanding Parkinson's: The microbiome and machine learning approach.

OBJECTIVE: Given that Parkinson's disease is a progressive disorder, with symptoms that worsen over ...

Real-Time Freezing of Gait Prediction and Detection in Parkinson's Disease.

Freezing of gait (FOG) is a walking disturbance that can lead to postural instability, falling, and ...

A pilot study for speech assessment to detect the severity of Parkinson's disease: An ensemble approach.

BACKGROUND: Changes in voice are a symptom of Parkinson's disease and used to assess the progression...

Machine Learning Recognizes Stages of Parkinson's Disease Using Magnetic Resonance Imaging.

Neurodegenerative diseases (NDs), such as Alzheimer's disease (AD) and Parkinson's disease (PD), are...

Protocol for artificial intelligence-guided neural control using deep reinforcement learning and infrared neural stimulation.

Closed-loop neural control is a powerful tool for both the scientific exploration of neural function...

Machine Learning and Statistical Analyses of Sensor Data Reveal Variability Between Repeated Trials in Parkinson's Disease Mobility Assessments.

Mobility tasks like the Timed Up and Go test (TUG), cognitive TUG (cogTUG), and walking with turns p...

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