Parkinson's Disease

Key Physicochemical Properties Dictating Gastrointestinal Bioaccessibility of Microplastics-Associated Organic Xenobiotics: Insights from a Deep Learning Approach.

A potential risk from human uptake of microplastics is the release of plastics-associated xenobiotic...

Classification of Parkinson's disease and essential tremor based on balance and gait characteristics from wearable motion sensors via machine learning techniques: a data-driven approach.

BACKGROUND: Parkinson's disease (PD) and essential tremor (ET) are movement disorders that can have ...

ODiNPred: comprehensive prediction of protein order and disorder.

Structural disorder is widespread in eukaryotic proteins and is vital for their function in diverse ...

A Methodology to Differentiate Parkinson's Disease and Aging Speech Based on Glottal Flow Acoustic Analysis.

Speech is controlled by axial neuromotor systems, therefore, it is highly sensitive to the effects o...

The effects of light touch cue on gait initiation in patients with Parkinson's disease.

INTRODUCTION: One of the common impairments in patients with Parkinson's disease (PD) is disturbance...

Linear predictive coding distinguishes spectral EEG features of Parkinson's disease.

OBJECTIVE: We have developed and validated a novel EEG-based signal processing approach to distingui...

Neural correlates of rehabilitation program with robot-assisted intensive therapy in one case of Holmes tremor.

Circular Shell Gripper for Handling Food Products.

Pneumatically driven soft robotic grippers have been extensively studied in recent years. A majority...

Morphological Characterization of Functional Brain Imaging by Isosurface Analysis in Parkinson's Disease.

Finding new biomarkers to model Parkinson's Disease (PD) is a challenge not only to help discerning ...

Identifying controllable cortical neural markers with machine learning for adaptive deep brain stimulation in Parkinson's disease.

The identification of oscillatory neural markers of Parkinson's disease (PD) can contribute not only...

Using Wearable Sensors and Machine Learning to Automatically Detect Freezing of Gait during a FOG-Provoking Test.

Freezing of gait (FOG) is a debilitating motor phenomenon that is common among individuals with adva...

A machine learning and network framework to discover new indications for small molecules.

Drug repurposing, identifying novel indications for drugs, bypasses common drug development pitfalls...

[Robot-assisted Mediastinal Mass Resection].

In recent years, robot-assisted thoracic surgery is gaining more and widespread interest in Europe. ...

Screening of Parkinsonian subtle fine-motor impairment from touchscreen typing via deep learning.

Fine-motor impairment (FMI) is progressively expressed in early Parkinson's Disease (PD) patients an...

Parkinson's disease detection from 20-step walking tests using inertial sensors of a smartphone: Machine learning approach based on an observational case-control study.

Parkinson's disease (PD) is a neurodegenerative disease inducing dystrophy of the motor system. Auto...

Diagnosing Parkinson Disease Through Facial Expression Recognition: Video Analysis.

BACKGROUND: The number of patients with neurological diseases is currently increasing annually, whic...

Evaluation of Vertical Ground Reaction Forces Pattern Visualization in Neurodegenerative Diseases Identification Using Deep Learning and Recurrence Plot Image Feature Extraction.

To diagnose neurodegenerative diseases (NDDs), physicians have been clinically evaluating symptoms. ...

Time-resolved neurotransmitter detection in mouse brain tissue using an artificial intelligence-nanogap.

The analysis of neurotransmitters in the brain helps to understand brain functions and diagnose Park...

Dynamical system based compact deep hybrid network for classification of Parkinson disease related EEG signals.

Electroencephalogram (EEG) signals accumulate the brain's spiking activities using standardized elec...

ResOT: Resource-Efficient Oblique Trees for Neural Signal Classification.

Classifiers that can be implemented on chip with minimal computational and memory resources are esse...

Decoding whole-genome mutational signatures in 37 human pan-cancers by denoising sparse autoencoder neural network.

Millions of somatic mutations have recently been discovered in cancer genomes. These mutations in ca...