IEEE transactions on bio-medical engineering
Feb 5, 2018
OBJECTIVE: Electrophysiological muscle classification (EMC) is a crucial step in the diagnosis of neuromuscular disorders. Existing quantitative techniques are not sufficiently robust and accurate to be reliably clinically used. Here, EMC is modeled ...
This paper proposes the design of a bipedal robotic controller where the function between the sensory input and motor output is treated as a black box derived from human data. In order to achieve this, we investigated the causal relationship between ...
Exploring neuroanatomical sex differences using a multivariate statistical learning approach can yield insights that cannot be derived with univariate analysis. While gross differences in total brain volume are well-established, uncovering the more s...
Journal of nutrigenetics and nutrigenomics
Feb 2, 2018
BACKGROUND/AIM: One of the beneficial effects associated with vitamin E intake is the enhancement of peroxisome proliferator-activated receptor gamma (PPARĪ³) activity and the consequent upregulation of adiponectin expression. The aim of this study wa...
PURPOSE: Breathing sounds during sleep are altered and characterized by various acoustic specificities in patients with sleep disordered breathing (SDB). This study aimed to identify acoustic biomarkers indicative of the severity of SDB by analyzing ...
OBJECTIVE: Lipid metabolism has been implicated in autoimmune disorders, but its relationship with anti-N-methyl-D-aspartate receptor (anti-NMDAR) encephalitis is unclear. This study examined the association of serum lipids with anti-NMDAR encephalit...
Most of the tools and diagnosis models of Masticatory Efficiency (ME) are not well documented or severely limited to simple image processing approaches. This study presents a novel expert system for ME assessment based on automatic recognition of mix...
In order to automatically identify a set of effective mammographic image features and build an optimal breast cancer risk stratification model, this study aims to investigate advantages of applying a machine learning approach embedded with a locally ...
The depression, anxiety and physiosomatic symptoms (DAPS) of schizophrenia are associated with negative symptoms and changes in tryptophan catabolite (TRYCAT) patterning. The aim of this study is to delineate the associations between DAPS and psychos...
OBJECTIVE: We investigated the potential of computer-based models to decode diagnosis and lifetime consumption in alcohol dependence (AD) from grey-matter pattern information. As machine-learning approaches to psychiatric neuroimaging have recently c...
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