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pro vyhledávání: '"Ortega-Martorell Sandra"'
We present several machine learning (ML) models developed to efficiently separate stars formed in-situ in Milky Way-type galaxies from those that were formed externally and later accreted. These models, which include examples from artificial neural n
Externí odkaz:
http://arxiv.org/abs/2405.00102
Autor:
Bellfield, Ryan A.A., Olier, Ivan, Lotto, Robyn, Jones, Ian, Dawson, Ellen A., Li, Guowei, Tuladhar, Anil M., Lip, Gregory Y.H., Ortega-Martorell, Sandra
Publikováno v:
In eBioMedicine September 2024 107
Autor:
Bellfield, Ryan A.A., Ortega-Martorell, Sandra, Lip, Gregory Y.H., Oxborough, David, Olier, Ivan
Publikováno v:
In Journal of Electrocardiology May-June 2024 84:17-26
Publikováno v:
In Trends in Cardiovascular Medicine
Akademický článek
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Akademický článek
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Publikováno v:
BMC Bioinformatics, Vol 13, Iss 1, p 38 (2012)
Abstract Background In-vivo single voxel proton magnetic resonance spectroscopy (SV 1H-MRS), coupled with supervised pattern recognition (PR) methods, has been widely used in clinical studies of discrimination of brain tumour types and follow-up of p
Externí odkaz:
https://doaj.org/article/61965960634446348e5c203d0ef9ca79
Publikováno v:
BMC Bioinformatics, Vol 11, Iss 1, p 106 (2010)
Abstract Background SpectraClassifier (SC) is a Java solution for designing and implementing Magnetic Resonance Spectroscopy (MRS)-based classifiers. The main goal of SC is to allow users with minimum background knowledge of multivariate statistics t
Externí odkaz:
https://doaj.org/article/95f13b6d0ae5410db2402ada7baba36e
Among interpretable machine learning methods, the class of Generalised Additive Neural Networks (GANNs) is referred to as Self-Explaining Neural Networks (SENN) because of the linear dependence on explicit functions of the inputs. In binary classific
Externí odkaz:
http://arxiv.org/abs/1908.05978
Autor:
Casaña-Eslava, Raúl V., Lisboa, Paulo J. G., Ortega-Martorell, Sandra, Jarman, Ian H., Martín-Guerrero, José D.
Quantum Clustering is a powerful method to detect clusters in data with mixed density. However, it is very sensitive to a length parameter that is inherent to the Schr\"odinger equation. In addition, linking data points into clusters requires local e
Externí odkaz:
http://arxiv.org/abs/1902.05578