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Robotic gait training in multiple sclerosis rehabilitation: Can virtual reality make the difference? Findings from a randomized controlled trial.

Journal of the neurological sciences
Gait, coordination, and balance may be severely compromised in patients with multiple sclerosis (MS), with considerable consequences on the patient's daily living activities, psychological status and quality of life. For this reason, MS patients may ...

Exploring types of play in an adapted robotics program for children with disabilities.

Disability and rehabilitation. Assistive technology
PURPOSE: Play is an important occupation in a child's development. Children with disabilities often have fewer opportunities to engage in meaningful play than typically developing children. The purpose of this study was to explore the types of play (...

Application of artificial neural network in medical geochemistry.

Environmental geochemistry and health
For the evaluation of various adverse health effects of chemical elements occurring in the environment on humans, the comparison and linking of geochemical data (chemical composition of groundwater, soils, and dusts) with data on health status of pop...

Discriminating cognitive status in Parkinson's disease through functional connectomics and machine learning.

Scientific reports
There is growing interest in the potential of neuroimaging to help develop non-invasive biomarkers in neurodegenerative diseases. In this study, connection-wise patterns of functional connectivity were used to distinguish Parkinson's disease patients...

Correlates of sleep quality in midlife and beyond: a machine learning analysis.

Sleep medicine
OBJECTIVES: In older adults, traditional metrics derived from polysomnography (PSG) are not well correlated with subjective sleep quality. Little is known about whether the association between PSG and subjective sleep quality changes with age, or whe...

A multi-resolution approach for spinal metastasis detection using deep Siamese neural networks.

Computers in biology and medicine
Spinal metastasis, a metastatic cancer of the spine, is the most common malignant disease in the spine. In this study, we investigate the feasibility of automated spinal metastasis detection in magnetic resonance imaging (MRI) by using deep learning ...

The mutational oncoprint of recurrent cytogenetic abnormalities in adult patients with de novo acute myeloid leukemia.

Leukemia
Recurrent chromosomal abnormalities and gene mutations detected at the time of diagnosis of acute myeloid leukemia (AML) are associated with particular disease features, treatment response and survival of AML patients, and are used to denote specific...

Automatic matching of surgeries to predict surgeons' next actions.

Artificial intelligence in medicine
OBJECTIVE: More than half a million surgeries are performed every day worldwide, which makes surgery one of the most important component of global health care. In this context, the objective of this paper is to introduce a new method for the predicti...

Distinguishing age-related cognitive decline from dementias: A study based on machine learning algorithms.

Journal of clinical neuroscience : official journal of the Neurosurgical Society of Australasia
BACKGROUND AND AIM: This study aims to examine the distinguishability of age-related cognitive decline (ARCD) from dementias based on some neurocognitive tests using machine learning.

Evaluating the diagnostic utility of applying a machine learning algorithm to diffusion tensor MRI measures in individuals with major depressive disorder.

Psychiatry research. Neuroimaging
Using MRI to diagnose mental disorders has been a long-term goal. Despite this, the vast majority of prior neuroimaging work has been descriptive rather than predictive. The current study applies support vector machine (SVM) learning to MRI measures ...