Latest AI and machine learning research in parkinson's disease for healthcare professionals.
The neuroimaging techniques such as dopaminergic imaging using Single Photon Emission Computed Tomog...
Quantitative susceptibility mapping (QSM) is based on magnetic resonance imaging (MRI) phase measure...
INTRODUCTION: A treatment response objective index (TRIS) was previously developed based on sensor d...
BACKGROUND AND OBJECTIVES: Parkinson's disease is a neurological disorder that affects the motor sys...
OBJECTIVE: The complex nature of Parkinson's disease (PD) makes difficult to rate its severity, main...
Neuromelanin sensitive magnetic resonance imaging (NMS-MRI) has been crucial in identifying abnormal...
Over the last years convolutional neural networks (CNNs) have shown remarkable results in different ...
INTRODUCTION: Parkinson's disease (PD) is a common neurodegenerative disorder characterized by disab...
Non-manifesting carriers (NMC) of the G2019S mutation in the LRRK2 gene represent an "at risk" group...
The assessment of Parkinson's disease (PD) poses a significant challenge, as it is influenced by var...
Quantitative susceptibility mapping (QSM) reveals pathological changes in widespread diseases such a...
BACKGROUND: Postural instability is a common disorder in Parkinson's disease (PD). The aim of this s...
Parkinson's disease is the second most prevalent neurodegenerative disorder in the Western world. It...
BACKGROUND: Robot-assisted gait training (RAGT) was developed to restore gait function by promoting ...
Parkinson's disease (PD) is a common neurodegenerative disorder that affects human's quality of life...
Adaptive deep brain stimulation (aDBS) is an emerging method to alleviate the side effects and impro...
Pars plana vitrectomy is a challenging, minimally invasive microsurgical procedure due to its intrin...
Modern robotics is an advanced minimally invasive technology with the advantages of wristed capabili...
Parkinson's Disease (PD) is one of the most prevalent neurodegenerative diseases that affects tens o...
In the recent 5Â years (2014-2018), there has been growing interest in the use of machine learning (M...
Machine learning algorithms that use data streams captured from soft wearable sensors have the poten...