Zobrazeno 1 - 10
of 115
pro vyhledávání: '"Lisboa, Paulo J G"'
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
Many of the current scientific advances in the life sciences have their origin in the intensive use of data for knowledge discovery. In no area this is so clear as in bioinformatics, led by technological breakthroughs in data acquisition technologies
Externí odkaz:
http://arxiv.org/abs/1802.09791
Autor:
Lisboa, Paulo J. G.1 (AUTHOR), Jayabalan, Manoj1 (AUTHOR), Ortega-Martorell, Sandra1 (AUTHOR), Olier, Ivan1 (AUTHOR), Medved, Dennis2 (AUTHOR), Nilsson, Johan2,3 (AUTHOR) johan.nilsson@med.lu.se
Publikováno v:
Scientific Reports. 11/14/2022, Vol. 12 Issue 1, p1-14. 14p.
Akademický článek
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Akademický článek
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Publikováno v:
Algorithms; Apr2023, Vol. 16 Issue 4, p181, 26p
Publikováno v:
Information Processing and Management of Uncertainty in Knowledge-Based Systems
Neural networks are frequently applied to medical data. We describe how complex and imbalanced data can be modelled with simple but accurate neural networks that are transparent to the user. In the case of a data set on cervical cancer with 753 obser
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=pmc_________::d3d26f3a02dd05647f6dfc3b146c4065
http://europepmc.org/articles/PMC7274310
http://europepmc.org/articles/PMC7274310
Publikováno v:
International Journal of Electronic Commerce, 2000 Jul 01. 4(4), 83-104.
Externí odkaz:
https://www.jstor.org/stable/27750950
Autor:
Ortega-Martorell, Sandra, Ruiz, Héctor, Vellido, Alfredo, Olier, Iván, Romero, Enrique, Julià Sapé, Ma. Margarita, Martín, José D., Jarman, Ian H., Arús i Caraltó, Carles, Lisboa, Paulo J. G., Universitat Autònoma de Barcelona. Institut de Biotecnologia i de Biomedicina \\'Vicent Villar Palasí\\'
Publikováno v:
Recercat: Dipósit de la Recerca de Catalunya
Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
Dipòsit Digital de Documents de la UAB
Universitat Autònoma de Barcelona
Recercat. Dipósit de la Recerca de Catalunya
instname
PLoS ONE, Vol 8, Iss 12, p e83773 (2013)
PLoS ONE Vol. 8 Issue 12
RODERIC. Repositorio Institucional de la Universitat de Valéncia
PLoS ONE
Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
Dipòsit Digital de Documents de la UAB
Universitat Autònoma de Barcelona
Recercat. Dipósit de la Recerca de Catalunya
instname
PLoS ONE, Vol 8, Iss 12, p e83773 (2013)
PLoS ONE Vol. 8 Issue 12
RODERIC. Repositorio Institucional de la Universitat de Valéncia
PLoS ONE
Background: The clinical investigation of human brain tumors often starts with a non-invasive imaging study, providing \ud information about the tumor extent and location, but little insight into the biochemistry of the analyzed tissue. Magnetic \ud
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d88bb97368518f1290dd67f07e858388
http://hdl.handle.net/2072/407808
http://hdl.handle.net/2072/407808