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pro vyhledávání: '"Maitane Martinez-Eguiluz"'
Autor:
Maitane Martinez-Eguiluz, Olatz Arbelaitz, Ibai Gurrutxaga, Javier Muguerza, Juan Carlos Gomez-Esteban, Iñigo Gabilondo, Ane Murueta-Goyena
Publikováno v:
Applied Sciences, Vol 14, Iss 18, p 8149 (2024)
Parkinson’s disease (PD) is a neurodegenerative disorder marked by motor and cognitive impairments. The early prediction of cognitive deterioration in PD is crucial. This work aims to predict the change in the Montreal Cognitive Assessment (MoCA) a
Externí odkaz:
https://doaj.org/article/3ab0bb74e721467cabf7600ea8d36f15
Autor:
Maitane Martinez-Eguiluz, Olatz Arbelaitz, Ibai Gurrutxaga, Javier Muguerza, Iñigo Perona, Ane Murueta-Goyena, Marian Acera, Rocío Del Pino, Beatriz Tijero, Juan Carlos Gomez-Esteban, Iñigo Gabilondo
Publikováno v:
Neural Computing and Applications. 35:5603-5617
Non-motor manifestations of Parkinson’s disease (PD) appear early and have a significant impact on the quality of life of patients, but few studies have evaluated their predictive potential with machine learning algorithms. We evaluated 9 algorithm
Autor:
Maria Luisa Jáuregui Abrisqueta, Javier Muguerza, Nagore Sagastibeltza, Asier Salazar-Ramirez, Raquel Suriá Martínez, Montserrat Cuadrado, Maitane Martinez-Eguiluz, Nora Cívicos Sánchez
Publikováno v:
CBMS
The main objective of this work is to perform a preliminary study of the potential of using physiological signals as biomarkers for the identification of Autonomic Dysreflexia (AD) in patients suffering from a spinal cord injury. For this purpose, a
Publikováno v:
Advances in Artificial Intelligence ISBN: 9783030857127
CAEPIA
CAEPIA
It is said that with great power comes great responsibility. Nowadays, we rely on machine learning systems to make decisions. Unfortunately these systems suffer from algorithmic biases; they often produce results that are systemically prejudiced due
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0256156617619c08d86f0dd16637cbf2
https://doi.org/10.1007/978-3-030-85713-4_9
https://doi.org/10.1007/978-3-030-85713-4_9