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Neurology

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Machine-Learning Classifier for Patients with Major Depressive Disorder: Multifeature Approach Based on a High-Order Minimum Spanning Tree Functional Brain Network.

Computational and mathematical methods in medicine
High-order functional connectivity networks are rich in time information that can reflect dynamic changes in functional connectivity between brain regions. Accordingly, such networks are widely used to classify brain diseases. However, traditional me...

Neurodegenerative disease: MRI biomarkers - a precision medicine tool in neurology?

Nature reviews. Neurology
Two new studies highlight the potential of neuroimaging to aid the differential diagnosis of neurodegenerative disease, for both clinical practice and emerging trials. Although this approach holds great promise, meaningful implementation of neuroimag...

Inferring Clinical Correlations from EEG Reports with Deep Neural Learning.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Successful diagnosis and management of neurological dysfunction relies on proper communication between the neurologist and the primary physician (or other specialists). Because this communication is documented within medical records, the ability to a...

Improving the Accuracy and Training Speed of Motor Imagery Brain-Computer Interfaces Using Wavelet-Based Combined Feature Vectors and Gaussian Mixture Model-Supervectors.

Sensors (Basel, Switzerland)
In this paper, we propose a set of wavelet-based combined feature vectors and a Gaussian mixture model (GMM)-supervector to enhance training speed and classification accuracy in motor imagery brain-computer interfaces. The proposed method is configur...

Deep Learning in Neuroradiology.

AJNR. American journal of neuroradiology
Deep learning is a form of machine learning using a convolutional neural network architecture that shows tremendous promise for imaging applications. It is increasingly being adapted from its original demonstration in computer vision applications to ...

Artificial intelligence in neurosciences: A clinician's perspective.

Neurology India
Even after making allowance for an unprecedented hype, it is an undeniable fact that, in the coming decade, deployment of Artificial Intelligence (AI) will cause a paradigm shift in the delivery of healthcare. This paper will review the practical uti...

Machine learning in neurology: what neurologists can learn from machines and vice versa.

Journal of neurology
Artificial intelligence is increasingly becoming a part of everyday life. This raises the question whether clinical neurology can benefit from these novel methods to increase diagnostic accuracy. Several recent studies have used machine learning clas...

[Neurological contact.].

Recenti progressi in medicina
To what extent is current clinical practice capable of gathering relevant patient data, observing them and giving them adequate information back? To what extent does the clinical pathway play a role of real care and not simply technology delivery? Th...