Zobrazeno 1 - 10
of 1 091
pro vyhledávání: '"Menardi, A."'
Autor:
Jihane Frikeche, Marion David, Xavier Mouska, Damien Treguer, Yue Cui, Sandrine Rouquier, Enora Lecorgne, Emma Proics, Papa Babacar Fall, Audrey Lafon, Gregory Lara, Alexandra Menardi, David Fenard, Tobias Abel, Julie Gertner-Dardenne, Maurus de la Rosa, Celine Dumont
Publikováno v:
Journal of Neuroinflammation, Vol 21, Iss 1, Pp 1-16 (2024)
Abstract Multiple sclerosis (MS) is an autoimmune disease affecting the central nervous system (CNS) with the immune system attacking myelin sheaths leading to neuronal death. While several disease-modifying therapies are available to treat MS, these
Externí odkaz:
https://doaj.org/article/b0d2facc0d0543fd93f28c1fda2eaf9c
Searching for as yet undetected gamma-ray sources is a major target of the Fermi LAT Collaboration. We present an algorithm capable of identifying such type of sources by non-parametrically clustering the directions of arrival of the high-energy phot
Externí odkaz:
http://arxiv.org/abs/2301.11332
Brain topology underlying executive functions across the lifespan: focus on the default mode network
Publikováno v:
Frontiers in Psychology, Vol 15 (2024)
IntroductionWhile traditional neuroimaging approaches to the study of executive functions (EFs) have typically employed task-evoked paradigms, resting state studies are gaining popularity as a tool for investigating inter-individual variability in th
Externí odkaz:
https://doaj.org/article/e9fcdead0da1426599d2e888f57a23a7
Autor:
Stakia, Anna, Dorigo, Tommaso, Banelli, Giovanni, Bortoletto, Daniela, Casa, Alessandro, de Castro, Pablo, Delaere, Christophe, Donini, Julien, Finos, Livio, Gallinaro, Michele, Giammanco, Andrea, Held, Alexander, Morales, Fabricio Jiménez, Kotkowski, Grzegorz, Liew, Seng Pei, Maltoni, Fabio, Menardi, Giovanna, Papavergou, Ioanna, Saggio, Alessia, Scarpa, Bruno, Strong, Giles C., Tosciri, Cecilia, Varela, João, Vischia, Pietro, Weiler, Andreas
Publikováno v:
Rev. Phys. 7 (2021) 100063
Between the years 2015 and 2019, members of the Horizon 2020-funded Innovative Training Network named "AMVA4NewPhysics" studied the customization and application of advanced multivariate analysis methods and statistical learning tools to high-energy
Externí odkaz:
http://arxiv.org/abs/2105.07530
Multivariate time-dependent data, where multiple features are observed over time for a set of individuals, are increasingly widespread in many application domains. To model these data we need to account for relations among both time instants and vari
Externí odkaz:
http://arxiv.org/abs/2104.03083
Autor:
Menardi, Giovanna
Publikováno v:
Statistical Analysis and Data Mining, 13(1), 83-97 (2020)
Image segmentation aims at identifying regions of interest within an image, by grouping pixels according to their properties. This task resembles the statistical one of clustering, yet many standard clustering methods fail to meet the basic requireme
Externí odkaz:
http://arxiv.org/abs/2101.08345
The idea underlying the modal formulation of density-based clustering is to associate groups with the regions around the modes of the probability density function underlying the data. This correspondence between clusters and dense regions in the samp
Externí odkaz:
http://arxiv.org/abs/2101.08334
Electrical Storm Induced by Cardiac Resynchronization: Efficacy of the Multipoint Pacing Stimulation
Publikováno v:
Diseases, Vol 12, Iss 5, p 105 (2024)
Although cardiac resynchronization therapy (CRT) reduces morbidity and mortality and reverses left ventricular (LV) remodeling in heart failure patients with LV electrical dyssynchrony, induced proarrhythmia has been reported. The mechanism of CRT-in
Externí odkaz:
https://doaj.org/article/3004b4c710b94723b41e0c9afe2e8354
The nonparametric formulation of density-based clustering, known as modal clustering, draws a correspondence between groups and the attraction domains of the modes of the density function underlying the data. Its probabilistic foundation allows for a
Externí odkaz:
http://arxiv.org/abs/2010.13440
Publikováno v:
Advances in Data Analysis and Classification (2020): 1-25
With the recent growth in data availability and complexity, and the associated outburst of elaborate modelling approaches, model selection tools have become a lifeline, providing objective criteria to deal with this increasingly challenging landscape
Externí odkaz:
http://arxiv.org/abs/1911.06726