Zobrazeno 1 - 10
of 108
pro vyhledávání: '"Vilaplana Besler, Verónica"'
Autor:
Vilaplana Besler, Verónica
Publikováno v:
TDX (Tesis Doctorals en Xarxa).
One of the central problems in computer vision is the automatic recognition of object classes. In particular, the detection of the class of human faces is a problem that generates special interest due to the large number of applications that require
Externí odkaz:
http://hdl.handle.net/10803/33330
Autor:
Hernández Pérez, Carlos, Pachón García, Cristian, Delicado Useros, Pedro Francisco, Vilaplana Besler, Verónica
In this study, we train and compare three types of machine learning algorithms for Survival Analysis: Random Survival Forest, DeepSurv and DeepHit, using the SEER database to model cutaneous malignant melanoma. Additionally, we employ SurvLIMEpy libr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______3484::d7824db13bb4594a5dfb0a2f58667589
https://hdl.handle.net/2117/390006
https://hdl.handle.net/2117/390006
Autor:
Cumplido Mayoral, Irene, García Prat, Marina, Operto, Grégory, Falcón Falcón, Carles, Shekari, Mahnaz, Cacciaglia, Raffaele, Milà Alomà, Marta, Lorenzini, Luigi, Ingala, Silvia, Vilaplana Besler, Verónica
Brain-age can be inferred from structural neuroimaging and compared to chronological age (brain-age delta) as a marker of biological brain aging. Accelerated aging has been found in neurodegenerative disorders like Alzheimer's disease (AD), but its v
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______3484::71f944ff880726bab81822985a970aa4
https://hdl.handle.net/2117/387009
https://hdl.handle.net/2117/387009
Autor:
Cumplido Mayoral, Irene, García Prat, Marina, Operto, Grégory, Falcón Falcón, Carles, Shekari, Mahnaz, Cacciaglia, Raffaele, Milà Alomà, Marta, Lorenzini, Luigi, Ingala, Silvia, Vilaplana Besler, Verónica
Background: Brain-age can be inferred from structural neuroimaging and compared to chronological age (brain-age delta), as a marker of accelerated/decelerated biological brain aging. Accelerated biological aging has been found in Alzheimer’s diseas
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______3484::e7c222012730d8aacac39295910c583f
https://hdl.handle.net/2117/381203
https://hdl.handle.net/2117/381203
Autor:
Mehta, Raghav, Filos, Angelos, Baid, Ujjwal, Sako, Chiharu, McKinley, Richard, Rebsamen, Michael, Dätwyler, Katrin, Meier, Raphael, Mora Ballestar, Laura, Vilaplana Besler, Verónica
Deep learning (DL) models have provided state-of-the-art performance in various medical imaging benchmarking challenges, including the Brain Tumor Segmentation (BraTS) chal- lenges. However, the task of focal pathology multi-compartment segmentation
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______3484::14f6ed2e222f02dc91fc8a32b72bbb72
https://hdl.handle.net/2117/383998
https://hdl.handle.net/2117/383998
Autor:
Cumplido Mayoral, Irene, García Prat, Marina, Operto, Grégory, Falcón, Carles, Shekari, Mahnaz, Cacciaglia, Raffaele, Milà Alomà, Marta, Lorenzini, Luigi, Ingala, Silvia, Vilaplana Besler, Verónica
Brain-age can be inferred from structural neuroimaging and compared to chronological age (brain-age delta) as a marker of biological brain aging. Accelerated aging has been found in neurodegenerative disorders like Alzheimer’s disease (AD), but its
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______3484::acafc8b9cb3c05f9b2fa39726f15bb25
https://www.medrxiv.org/content/10.1101/2022.06.23.22276492v1
https://www.medrxiv.org/content/10.1101/2022.06.23.22276492v1
Autor:
Pina Benages, Òscar, Cumplido Mayoral, Irene, Cacciaglia, Raffaele, González-de-Echávarri, Jose María, Gispert López, Juan Domingo, Vilaplana Besler, Verónica
Biological networks have gained considerable attention within the Deep Learning community because of the promising framework of Graph Neural Networks (GNN), neural models that operate in complex networks. In the context of neuroimaging, GNNs have suc
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______3484::34f6ea62742cb3a7eb0225575afebd02
https://hdl.handle.net/2117/383999
https://hdl.handle.net/2117/383999
In this manuscript we propose a framework for the analysis of whole slide images (WSI) on the cell entity space with self-supervised deep learning on graphs and explore its representation quality at different levels of application. It consists of a t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______3484::7350f83e9e8e472268b3f3f3a353c9ec
https://hdl.handle.net/2117/384000
https://hdl.handle.net/2117/384000
Autor:
Cumplido Mayoral, Irene, Shekari, Mahnaz, Salvado, Gemma, Operto, Grégory, Cacciaglia, Raffaele, Falcón, Carles, Niñerola Baizán, Aida, Perissinotti, Andrés, Minguillón, Carolina, Vilaplana Besler, Verónica|||0000-0001-6924-9961
Publikováno v:
UPCommons. Portal del coneixement obert de la UPC
Universitat Politècnica de Catalunya (UPC)
Universitat Politècnica de Catalunya (UPC)
Background: CSF Aß42 is thought to show AD-related alterations earlier than amyloid-ß PET. Therefore, cognitively unimpaired (CU) individuals with abnormal CSF Aß42 and normal amyloid-ß PET are believed to be in the earliest stages of the AD cont
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::565ae1b3cddad89bd126f32fcd9e333d
https://hdl.handle.net/2117/363800
https://hdl.handle.net/2117/363800
Autor:
Cumplido Mayoral, Irene, Ingala, Silvia, Lorenzini, Luigi, Wink, Alle Meije, Haller, Sven, Molinuevo Guix, Jose Luis, Wolz, Robin, Palombit, Alessandro, Schwarz, Adam J., Vilaplana Besler, Verónica|||0000-0001-6924-9961
Publikováno v:
UPCommons. Portal del coneixement obert de la UPC
Universitat Politècnica de Catalunya (UPC)
Universitat Politècnica de Catalunya (UPC)
Background: Structural MRI measurements can contribute to the prediction of amyloid pathology in cognitively unimpaired (CU) individuals. In this work, we aimed at studying the predictive capacity, robustness, and generalizability of ML techniques to
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::62a93093b2f100fde4559287fb91c0c1
https://hdl.handle.net/2117/363798
https://hdl.handle.net/2117/363798