Neurology

Parkinson's Disease

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

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Identification of an early-stage Parkinson's disease neuromarker using event-related potentials, brain network analytics and machine-learning.

OBJECTIVE: The purpose of this study is to explore the possibility of developing a biomarker that ca...

Robotically-induced hallucination triggers subtle changes in brain network transitions.

The perception that someone is nearby, although nobody can be seen or heard, is called presence hall...

Robotics, automation, active electrode arrays, and new devices for cochlear implantation: A contemporary review.

In the last two decades, cochlear implant surgery has evolved into a minimally invasive, hearing pre...

Deep learning reveals personalized spatial spectral abnormalities of high delta and low alpha bands in EEG of patients with early Parkinson's disease.

Parkinson's disease (PD) is one of the most common neurodegenerative diseases, and early diagnosis i...

Current status of robot-assisted minimally invasive esophagectomy: what is the real benefit?

Robot-assisted minimally invasive esophagectomy (RAMIE) for esophageal cancer has been performed inc...

Data-driven identification of diagnostically useful extrastriatal signal in dopamine transporter SPECT using explainable AI.

This study used explainable artificial intelligence for data-driven identification of extrastriatal ...

Effect of data leakage in brain MRI classification using 2D convolutional neural networks.

In recent years, 2D convolutional neural networks (CNNs) have been extensively used to diagnose neur...

Self-paced learning and privileged information based KRR classification algorithm for diagnosis of Parkinson's disease.

Computer aided diagnosis (CAD) methods for Parkinson's disease (PD) can assist clinicians in diagnos...

Tensegrity Robotics.

Numerous recent advances in robotics have been inspired by the biological principle of tensile integ...

Application of Deep Learning Models for Automated Identification of Parkinson's Disease: A Review (2011-2021).

Parkinson's disease (PD) is the second most common neurodegenerative disorder affecting over 6 milli...

Bioinspired soft microrobots actuated by magnetic field.

In contrast to traditional large-scale robots, which require complicated mechanical joints and mater...

Non-invasive diagnostic tool for Parkinson's disease by sebum RNA profile with machine learning.

Parkinson's disease (PD) is a progressive neurodegenerative disease presenting with motor and non-mo...

Brain emotional learning impedance control of uncertain nonlinear systems with time delay: Experiments on a hybrid elastic joint robot in telesurgery.

Telesurgical robot control is a significant example of an uncertain nonlinear system, as it involves...

Use of machine learning method on automatic classification of motor subtype of Parkinson's disease based on multilevel indices of rs-fMRI.

OBJECTIVE: This study aimed to develop an automatic classifier to distinguish different motor subtyp...

Discovery of Parkinson's disease states and disease progression modelling: a longitudinal data study using machine learning.

BACKGROUND: Parkinson's disease is heterogeneous in symptom presentation and progression. Increased ...

Early balance impairment in Parkinson's Disease: Evidence from Robot-assisted axial rotations.

OBJECTIVE: Early postural instability (PI) is a red flag for the diagnosis of Parkinson's disease (P...

Robotics and future technical developments in pediatric urology.

Minimally invasive surgery (MIS) has represented the main innovation in the field of pediatric surge...

PassFlow: a multimodal workflow for predicting deep brain stimulation outcomes.

PURPOSE: Deep Brain Stimulation (DBS) is a proven therapy for Parkinson's Disease (PD), frequently r...

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