Results 31 to 40 of about 845,859 (278)
Diagnostics, 2023 This paper uses EEG data to introduce an approach for classifying right and left-hand classes in Motor Imagery (MI) tasks. The Kernel Cross-Spectral Functional Connectivity Network (KCS-FCnet) method addresses these limitations by providing richer ...
Daniel Guillermo García-Murillo +2 more
doaj +1 more source
International Journal of Big Data and Analytics in Healthcare, 2021 In the healthcare industry, sources look after different customers with diverse diseases and complications. Thus, at the source, a great amount of data in all aspects like status of the patients, behaviour of the diseases, etc. are collected, and now it becomes the job of the practitioner at source to use the available data for diagnosing the diseases ...
Arti Saxena, Vijay Kumar
openaire +2 more sources
A Data-Driven Measure of Effective Connectivity Based on Renyi's α-Entropy
Frontiers in Neuroscience, 2019 Transfer entropy (TE) is a model-free effective connectivity measure based on information theory. It has been increasingly used in neuroscience because of its ability to detect unknown non-linear interactions, which makes it well suited for exploratory ...
Ivan De La Pava Panche +2 more
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A feasible k-means kernel trick under non-Euclidean feature space
International Journal of Applied Mathematics and Computer Science, 2020 This paper poses the question of whether or not the usage of the kernel trick is justified. We investigate it for the special case of its usage in the kernel k-means algorithm.
Kłopotek Robert +2 more
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Locally linear approximation for Kernel methods : the Railway Kernel [PDF]
, 2008 In this paper we present a new kernel, the Railway Kernel, that works properly for general (nonlinear) classification problems, with the interesting property that acts locally as a linear kernel.
González, Javier, Muñoz, Alberto
core +1 more source
Network Localization of Fatigue in Multiple Sclerosis
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Background Fatigue is among the most common symptoms and one of the main factors determining the quality of life in multiple sclerosis (MS). However, the neurobiological mechanisms underlying fatigue are not fully understood. Here we studied lesion locations and their connections in individuals with MS, aiming to identify brain networks ...
Olli Likitalo +12 more
wiley +1 more source
Applied SciencesSoftware-defined networking (SDN) requires adaptive control strategies to handle dynamic traffic conditions and heterogeneous network environments.
Yedil Nurakhov +3 more
doaj +1 more source
Learning latent functions for causal discovery
Machine Learning: Science and Technology, 2023 Causal discovery from observational data offers unique opportunities in many scientific disciplines: reconstructing causal drivers, testing causal hypotheses, and comparing and evaluating models for optimizing targeted interventions.
Emiliano Díaz +3 more
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Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Peripheral neuropathies contribute to patient disability but may be diagnosed late or missed altogether due to late referral, limitation of current diagnostic methods and lack of specialized testing facilities. To address this clinical gap, we developed NeuropathAI, an interpretable deep learning–based multiclass classification ...
Chaima Ben Rabah +7 more
wiley +1 more source
Entropy, 2020 Multiple kernel learning is a paradigm which employs a properly constructed chain of kernel functions able to simultaneously analyse different data or different representations of the same data.
Alessio Martino +3 more
doaj +1 more source