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Deep Learning Corpus Callosum Segmentation as a Neurodegenerative Marker in Multiple Sclerosis.
Journal of neuroimaging : official journal of the American Society of Neuroimaging
Feb 15, 2021
BACKGROUND AND PURPOSE: Corpus callosum atrophy is a sensitive biomarker of multiple sclerosis (MS) neurodegeneration but typically requires manual 2D or volumetric 3D-based segmentations. We developed a supervised machine learning algorithm, DeepnCC...
Reliability modelling of resting-state functional connectivity.
NeuroImage
Feb 11, 2021
Resting-state functional magnetic resonance imaging (rs-fMRI) has an inherently low signal-to-noise ratio largely due to thermal and physiological noise that attenuates the functional connectivity (FC) estimates. Such attenuation limits the reliabili...
A deep learning-based method for grip strength prediction: Comparison of multilayer perceptron and polynomial regression approaches.
PloS one
Feb 11, 2021
The objective of this study was to accurately predict the grip strength using a deep learning-based method (e.g., multi-layer perceptron [MLP] regression). The maximal grip strength with varying postures (upper arm, forearm, and lower body) of 164 yo...
Application of machine learning to the identification of joint degrees of freedom involved in abnormal movement during upper limb prosthesis use.
PloS one
Feb 11, 2021
To evaluate movement quality of upper limb (UL) prosthesis users, performance-based outcome measures have been developed that examine the normalcy of movement as compared to a person with a sound, intact hand. However, the broad definition of "normal...
Whole-brain modelling of resting state fMRI differentiates ADHD subtypes and facilitates stratified neuro-stimulation therapy.
NeuroImage
Feb 10, 2021
Recent advances in non-linear computational and dynamical modelling have opened up the possibility to parametrize dynamic neural mechanisms that drive complex behavior. Importantly, building models of neuronal processes is of key importance to fully ...
Radiomic Machine Learning Classifiers in Spine Bone Tumors: A Multi-Software, Multi-Scanner Study.
European journal of radiology
Feb 10, 2021
PURPOSE: Spinal lesion differential diagnosis remains challenging even in MRI. Radiomics and machine learning (ML) have proven useful even in absence of a standardized data mining pipeline. We aimed to assess ML diagnostic performance in spinal lesio...
Discrimination of malignant from benign thyroid lesions through neural networks using FTIR signals obtained from tissues.
Analytical and bioanalytical chemistry
Feb 10, 2021
The current gold standard in cancer diagnosis-the microscopic examination of hematoxylin and eosin (H&E)-stained biopsies-is prone to bias since it greatly relies on visual examination. Hence, there is a need to develop a more sensitive and specific ...
How Robots Help Nurses Focus on Professional Task Engagement and Reduce Nurses' Turnover Intention.
Journal of nursing scholarship : an official publication of Sigma Theta Tau International Honor Society of Nursing
Feb 10, 2021
PURPOSE: To examine how robot-enabled focus on professional task engagement and robot-reduced nonprofessional task engagement are related to nurses' professional turnover intention.
Prediction of Phakic Intraocular Lens Vault Using Machine Learning of Anterior Segment Optical Coherence Tomography Metrics.
American journal of ophthalmology
Feb 9, 2021
PURPOSE: To compare the achieved vault using the conventional manufacturer's nomogram and the predicted vault using machine learning, in a large cohort of eyes undergoing posterior chamber phakic intraocular lens (EVO implantable collamer lens [ICL];...
How hot is the hot zone? Computational modelling clarifies the role of parietal and frontoparietal connectivity during anaesthetic-induced loss of consciousness.
NeuroImage
Feb 9, 2021
In recent years, specific cortical networks have been proposed to be crucial for sustaining consciousness, including the posterior hot zone and frontoparietal resting state networks (RSN). Here, we computationally evaluate the relative contributions ...
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