Latest AI and machine learning research in neurology for healthcare professionals.
Support vector machines are powerful tools used to solve the small sample and nonlinear classification problems, but their ultimate classification performance depends heavily upon the selection of appropriate kernel and penalty parameters. In this study, we propose using a particle swarm optimization algorithm to optimize the selection of both the kernel and penalty parameters in order to improve ...
New neuroimaging techniques have led to significant advancements in our understanding of cerebral mechanisms of primary insomnia. However, the neuronal low-frequency oscillation remains largely uncharacterized in chronic primary insomnia (CPI). In this study, the amplitude of low-frequency fluctuation (ALFF), a data-driven method based on resting-state functional MRI, was used to examine local int...
BACKGROUND: Patients affected by mild stroke benefit more from physiological overground walking training than walking-like training performed in place...
BACKGROUND: Neuropathy often occurs following drug treatment such as chemotherapy. Severe instances of neuropathy can result in cessation of life-savi...
The aim of this study was to validate a novel classification for the diagnosis of PNESs. Fifty-five PNES video-EEG recordings were retrospectively ana...
Stroke is one of the most common causes of death, only second to heart disease. Molecular investigations about stroke are in acute shortage nowadays. ...
Body weight support (BWS) promotes better functional outcomes for neurologically challenged patients. Despite the established effectiveness of BWS in ...
OBJECTIVE: To develop mathematical models for predicting level of independence with specific functional outcomes 1 year after discharge from inpatient...
Recent resting-state functional MRI investigations have demonstrated that much of the large-scale functional network architecture supporting motor, se...
BACKGROUND: In the United States, 795,000 people suffer strokes each year; 10-15Â % of these strokes can be attributed to stenosis caused by plaque in ...
Stereotactic radiosurgery (SRS) is the accurate, conformal delivery of high-dose radiation to well-defined targets while minimizing normal structure d...
In this paper a novel flexible joint is proposed for robotic fish pectoral fins, which enables a swimming behavior emulating the fin motions of many a...
In spite of several decades of intensive research and development, the existing algorithms of myoelectric pattern recognition (MPR) are yet to make si...
A novel technique of quantitative EEG for differentiating patients with early-stage Creutzfeldt-Jakob disease (CJD) from other forms of rapidly progre...
The identification of the temporal variations in human operator cognitive task-load (CTL) is crucial for preventing possible accidents in human-machin...
Extreme learning machine (ELM) is an effective machine learning technique with simple theory and fast implementation, which has gained increasing inte...
BACKGROUND: Brain MRI holds promise to gauge different aspects of Parkinson's disease (PD)-related pathological changes. Its analysis, however, is hin...
Two new studies highlight the potential of neuroimaging to aid the differential diagnosis of neurodegenerative disease, for both clinical practice and...
An intelligent rollator (IRO) was developed that aims at obstacle detection and guidance to avoid collisions and accidental falls. The IRO is a retrof...
Sparse learning has been widely investigated for analysis of brain images to assist the diagnosis of Alzheimer's disease and its prodromal stage, i.e....