Zobrazeno 1 - 10
of 34
pro vyhledávání: '"Jose L. Ayala"'
Autor:
Laura Hernández-Lorenzo, Fernando García-Gutiérrez, Ana Solbas-Casajús, Silvia Corrochano, Jordi A. Matías-Guiu, Jose L. Ayala
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-14 (2024)
Abstract Alzheimer's disease (AD) shows a high pathological and symptomatological heterogeneity. To study this heterogeneity, we have developed a patient stratification technique based on one of the most significant risk factors for the development o
Externí odkaz:
https://doaj.org/article/73528481fabb427199a0c3c582a39d51
Autor:
Laura Hernández-Lorenzo, Fernando García-Gutiérrez, Ana Solbas-Casajús, Silvia Corrochano, Jordi A. Matías-Guiu, Jose L. Ayala
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-1 (2024)
Externí odkaz:
https://doaj.org/article/53358be62bb04cb0a2448b87995f43f5
Autor:
Laura Hernández-Lorenzo, Markus Hoffmann, Evelyn Scheibling, Markus List, Jordi A. Matías-Guiu, Jose L. Ayala
Publikováno v:
Scientific Reports, Vol 12, Iss 1, Pp 1-13 (2022)
Abstract Alzheimer's disease (AD) is a neurodegenerative disease whose molecular mechanisms are activated several years before cognitive symptoms appear. Genotype-based prediction of the phenotype is thus a key challenge for the early diagnosis of AD
Externí odkaz:
https://doaj.org/article/aaf51446d8694603b4b659a20ab94bf5
Autor:
Noelia Esteban-García, Luis C. Fernández-Beltrán, Juan Miguel Godoy-Corchuelo, Jose L. Ayala, Jordi A. Matias-Guiu, Silvia Corrochano
Publikováno v:
Frontiers in Aging Neuroscience, Vol 14 (2022)
ObjectiveFrontotemporal dementia (FTD) and amyotrophic lateral sclerosis (ALS) are two distinct degenerative disorders with overlapping genetics, clinical manifestations, and pathology, including the presence of TDP-43 aggregates in nearly 50% of pat
Externí odkaz:
https://doaj.org/article/9a87c2cbfc0140b3ac3fef8cfed965e7
Autor:
Franklin Parrales Bravo, Alberto A. Del Barrio Garcia, Ana Beatriz Gago Veiga, Maria Mercedes Gallego De La Sacristana, Marina Ruiz Pinero, Angel Guerrero Peral, Saso Dzeroski, Jose L. Ayala
Publikováno v:
IEEE Access, Vol 7, Pp 92598-92614 (2019)
Deciding on the continuous treatment of chronic diseases is vital in terms of economy, quality of life, and time. We present a holistic data mining approach that addresses the prediction of the therapeutic response in a panoramic and feedback way whi
Externí odkaz:
https://doaj.org/article/f1d8fcb2893b419295782aae8e842a6e
Publikováno v:
Sensors, Vol 12, Iss 11, Pp 15088-15118 (2012)
Instruction memory organisations are pointed out as one of the major sources of energy consumption in embedded systems. As these systems are characterised by restrictive resources and a low-energy budget, any enhancement in this component allows not
Externí odkaz:
https://doaj.org/article/d0a554f90065421f9d00d059c812de35
Publikováno v:
Sensors, Vol 12, Iss 8, Pp 10659-10677 (2012)
Ubiquitous sensor network deployments, such as the ones found in Smart cities and Ambient intelligence applications, require constantly increasing high computational demands in order to process data and offer services to users. The nature of these ap
Externí odkaz:
https://doaj.org/article/424226b3b6784a3e95784a08a48c3bc6
Autor:
Javier Galvez-Goicuria, Josue Pagan, Lucia Perez, Julian Catalina-Gomez, Jose M. Moya, Jose L. Ayala
Publikováno v:
2022 IEEE International Conference on Omni-layer Intelligent Systems (COINS).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4ac0674c184f48bd405c54c70bf9509d
https://doi.org/10.1109/coins54846.2022.9854954
https://doi.org/10.1109/coins54846.2022.9854954
Publikováno v:
2022 IEEE International Conference on Omni-layer Intelligent Systems (COINS).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b7380c02860415fd96d2b5623337503f
https://doi.org/10.1109/coins54846.2022.9855010
https://doi.org/10.1109/coins54846.2022.9855010
Autor:
Fernando García-Gutiérrez, Laura Hernández-Lorenzo, María Nieves Cabrera-Martín, Jordi A. Matias-Guiu, José L. Ayala
Publikováno v:
NeuroImage, Vol 297, Iss , Pp 120695- (2024)
Background:: The prediction of Alzheimer’s disease (AD) progression from its early stages is a research priority. In this context, the use of Artificial Intelligence (AI) in AD has experienced a notable surge in recent years. However, existing inve
Externí odkaz:
https://doaj.org/article/dc33f3b4145c447da412ef35084f15ae