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Microstate and Omega Complexity Analyses of the Resting-state Electroencephalography06:40

Microstate and Omega Complexity Analyses of the Resting-state Electroencephalography

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This article describes the protocol underlying electroencephalography (EEG) microstate analysis and omega complexity analysis, which are two reference-free EEG measures and highly valuable to explore the neural mechanisms of brain...
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Constructing and Visualizing Models using Mime-based Machine-learning Framework06:19

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Mime is a flexible computational framework to construct a machine learning-based integration model with elegant performance. Here, we provide a detailed step-by-step procedure for developing predictive models with high accuracy, leveraging complex datasets to identify critical genes associated with disease progression, patient outcomes, and therapeutic response.
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Observing the Transformation of Bodily Self-consciousness in the Squeeze-machine Experiment07:20

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The squeeze machine, a V-shaped device that provides pressure along the whole body is used in therapy especially for people with autism. Here, we focus on its possible use in experiments to capture the typical transformations of bodily self-consciousness with peri-personal space...
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This study employed voice signal analysis and machine learning methods, utilizing MATLAB to extract distinctive voice features for non-invasive early detection of asthma. The Support Vector Machine (SVM) and Random Forest (RF) algorithms demonstrated comparable performance in terms of overall classification accuracy, although SVM may achieve a better balance between sensitivity and...
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Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model07:15

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model

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This protocol was designed to train a machine learning algorithm to use a combination of imaging parameters derived from magnetic resonance imaging (MRI) and positron emission tomography/computed tomography (PET/CT) in a rat model of breast cancer bone metastases to detect early metastatic disease and predict subsequent progression to...
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This methodology produces decision trees that target population groups more prone to suffering from mild cognitive impairment and are useful for cost-effective selective screening of the...
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Microstate and Omega Complexity Analyses of the Resting-state Electroencephalography
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Microstate and Omega Complexity Analyses of the Resting-state Electroencephalography

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機械学習はマイクロステートのサンプリング方法を変革する

Mark E Tuckerman1

  • 1Department of Chemistry and Courant Institute of Mathematical Sciences, New York University, New York, NY 10003, USA, and NYU-ECNU Center for Computational Chemistry at NYU Shanghai, Shanghai 200062, China. mark.tuckerman@nyu.edu.

Science (New York, N.Y.)
|September 7, 2019
PubMed
まとめ

No abstract available in PubMed .

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関連する実験動画

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