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pro vyhledávání: '"Bibas, A."'
Complementary item recommendations are a ubiquitous feature of modern e-commerce sites. Such recommendations are highly effective when they are based on collaborative signals like co-purchase statistics. In certain online marketplaces, however, e.g.,
Externí odkaz:
http://arxiv.org/abs/2303.05812
Autor:
Isaac de Faria Soares Rodrigues, Paulo Francisco Guerreiro Cardoso, Natalia Aparecida Nepomuceno da Silva, Aristides Tadeu Correia, Helio Minamoto, Benoit Jacques Bibas, Natalia de Souza Xavier Costa, Marilia Wellichan Mancini, Marisa Dolhnikoff, Paulo Manuel Pego-Fernandes
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-9 (2024)
Abstract To compare two different wavelengths of the surgical contact diode laser (CDL) for producing a posterior laryngofissure in in-vivo pigs. Anesthetized pigs underwent a tracheostomy and an anterior laryngofissure through a cervicotomy. They we
Externí odkaz:
https://doaj.org/article/819c6ebbfed64dd4a29e5febb62e9d9a
Automatically understanding the contents of an image is a highly relevant problem in practice. In e-commerce and social media settings, for example, a common problem is to automatically categorize user-provided pictures. Nowadays, a standard approach
Externí odkaz:
http://arxiv.org/abs/2210.11907
Autor:
Anne G. M. Schilder, Stephan Wolpert, Shakeel Saeed, Leonie M. Middelink, Albert S. B. Edge, Helen Blackshaw, REGAIN Consortium, Kostas Pastiadis, Athanasios G. Bibas
Publikováno v:
Nature Communications, Vol 15, Iss 1, Pp 1-9 (2024)
Abstract Inhibition of Notch signalling with a gamma-secretase inhibitor (GSI) induces mammalian hair cell regeneration and partial hearing restoration. In this proof-of-concept Phase I/IIa multiple-ascending dose open-label trial (ISRCTN59733689), a
Externí odkaz:
https://doaj.org/article/c507482871e1458b9e7192e6aabb92b2
Autor:
Bibas, Koby, Feder, Meir
In supervised batch learning, the predictive normalized maximum likelihood (pNML) has been proposed as the min-max regret solution for the distribution-free setting, where no distributional assumptions are made on the data. However, the pNML is not d
Externí odkaz:
http://arxiv.org/abs/2206.08757
Publikováno v:
Mediterranean Journal of Hematology and Infectious Diseases, Vol 16, Iss 1 (2024)
Waldenström macroglobulinemia (WM) is an infrequent variant of lymphoma, classified as a B-cell malignancy identified by the presence of IgM paraprotein, infiltration of clonal, small lymphoplasmacytic B cells in the bone marrow, and the MYD88 L265P
Externí odkaz:
https://doaj.org/article/83e1a80094f944cb857c8ec0a5e73d97
Detecting out-of-distribution (OOD) samples is vital for developing machine learning based models for critical safety systems. Common approaches for OOD detection assume access to some OOD samples during training which may not be available in a real-
Externí odkaz:
http://arxiv.org/abs/2110.09246
Adversarial attacks have been shown to be highly effective at degrading the performance of deep neural networks (DNNs). The most prominent defense is adversarial training, a method for learning a robust model. Nevertheless, adversarial training does
Externí odkaz:
http://arxiv.org/abs/2109.01945
Autor:
Valérie Chamouard, Julie Freyssenge, Béatrice Clairaz-Mahiou, Felicia Ferrera Bibas, Laurie Fraticelli
Publikováno v:
JMIR Formative Research, Vol 8, p e54656 (2024)
BackgroundSince June 2021, patients with hemophilia A with antifactor VIII inhibitors and those with severe hemophilia A without antifactor VIII inhibitors treated with Hemlibra have had to choose between a community or hospital pharmacy. The French
Externí odkaz:
https://doaj.org/article/87aae533a9094fc7945ae4923e1be17e
Autor:
Michele Bibas
Publikováno v:
Mediterranean Journal of Hematology and Infectious Diseases, Vol 16, Iss 1 (2024)
The objective of this two-part review is to present a current and comprehensive understanding of the diagnosis and management of plasmablastic lymphoma. The first part, which was published previously, focused on the study of epidemiology, etiology, c
Externí odkaz:
https://doaj.org/article/ead7e6ee00c9494283baae7c343f3f83