Latest AI and machine learning research in parkinson's disease for healthcare professionals.
The aggregation of alpha-synuclein (αS), natively unstructured presynaptic protein, is a crucial fac...
Parkinson disease (PD) is prevalent in elderly individuals and is characterized by selective degener...
OBJECTIVES: Various exercise strategies have been suggested to address movement deficits in order to...
The efficacy of deep brain stimulation (DBS) for Parkinson's disease (PD) depends in part on the pos...
OBJECTIVE: The study of gait in Parkinson's disease is important because it can provide insights int...
BACKGROUND AND PURPOSE: In this study we attempt to automatically classify individual patients with ...
The goal of this study was to develop an algorithm that automatically quantifies motor states (off, ...
BACKGROUND AND OBJECTIVE: A new expert system is proposed to discriminate healthy people from people...
MOTIVATION: Although clinical aspirations for new technology to accurately measure and diagnose Park...
Decoding neural activities related to voluntary and involuntary movements is fundamental to understa...
In this work, a fuzzy inference model to evaluate hands pronation/supination exercises during the MD...
The adaptation of the CRISPR-Cas9 system as a genome editing technique has generated much excitement...
BACKGROUND: Classification of human behavior from brain signals has potential application in develop...
With the goal of robustly designing and fabricating a soft robot based on a caterpillar featuring sh...
Retinal vein cannulation is a technically demanding surgical procedure where therapeutic agents are ...
Dopaminergic degeneration is a pathologic hallmark of Parkinson's disease (PD), which can be assesse...
Automatic food image recognition systems are alleviating the process of food-intake estimation and d...
Like their natural counterparts, soft bioinspired robots capable of actively tuning their mechanical...
Analysis of quantified voice patterns is useful in the detection and assessment of dysphonia and rel...
Patient condition during rehabilitation has been traditionally assessed using clinical scales. These...
Machine learning methods have been widely used in recent years for detection of neuroimaging biomark...