Zobrazeno 1 - 10
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pro vyhledávání: '"Quilez, P"'
Multivariate spatial disease mapping has become a pivotal part of everyday practice in social epidemiology. Despite the existence of several specifications for the relation between different outcomes, there is still a need for a new strategy that foc
Externí odkaz:
http://arxiv.org/abs/2410.21227
Changes in land use patterns have significant environmental and socioeconomic impacts, making it crucial for policymakers to understand their causes and consequences. This study, part of the European LAMASUS (Land Management for Sustainability) proje
Externí odkaz:
http://arxiv.org/abs/2407.21695
Combining data has become an indispensable tool for managing the current diversity and abundance of data. But, as data complexity and data volume swell, the computational demands of previously proposed models for combining data escalate proportionall
Externí odkaz:
http://arxiv.org/abs/2406.08174
Publikováno v:
Phys. Rev. D 110, 015024 (2024)
We compute the one-loop contribution to the $\bar{\theta}$-parameter of an axion-like particle (ALP) with CP-odd derivative couplings. Its contribution to the neutron electric dipole moment is shown to be orders of magnitude larger than that stemming
Externí odkaz:
http://arxiv.org/abs/2403.12133
We elaborate how to apply the Hilbert series method to enumerating group covariants, which transform under any given representation, including but going beyond group invariants. Mathematically, group covariants form a module over the ring of the inva
Externí odkaz:
http://arxiv.org/abs/2312.13349
Autor:
Rolfsnes, Erlend Sortland, Thangngat, Philip, Eftestøl, Trygve, Nordström, Tobias, Jäderling, Fredrik, Eklund, Martin, Fernandez-Quilez, Alvaro
Magnetic resonance imaging has evolved as a key component for prostate cancer (PCa) detection, substantially increasing the radiologist workload. Artificial intelligence (AI) systems can support radiological assessment by segmenting and classifying l
Externí odkaz:
http://arxiv.org/abs/2309.08381
Publikováno v:
Nature Communications, Vol 15, Iss 1, Pp 1-10 (2024)
Abstract The growing global food demand, coupled with the limitations of traditional pest control methods, has driven the search for innovative and sustainable solutions in agricultural pest management. In this review, we highlight polymeric nanocarr
Externí odkaz:
https://doaj.org/article/15a2bc7d16204ccb86b3c4fb0020f717
Autor:
Fernandez-Quilez, Alvaro, Vidziunas, Linas, Thoresen, Ørjan Kløvfjell, Oppedal, Ketil, Kjosavik, Svein Reidar, Eftestøl, Trygve
Traditional deep learning (DL) approaches based on supervised learning paradigms require large amounts of annotated data that are rarely available in the medical domain. Unsupervised Out-of-distribution (OOD) detection is an alternative that requires
Externí odkaz:
http://arxiv.org/abs/2308.06481
Leveraging multi-view data without annotations for prostate MRI segmentation: A contrastive approach
Autor:
Lindeijer, Tim Nikolass, Ytredal, Tord Martin, Eftestøl, Trygve, Nordström, Tobias, Jäderling, Fredrik, Eklund, Martin, Fernandez-Quilez, Alvaro
An accurate prostate delineation and volume characterization can support the clinical assessment of prostate cancer. A large amount of automatic prostate segmentation tools consider exclusively the axial MRI direction in spite of the availability as
Externí odkaz:
http://arxiv.org/abs/2308.06477
Autor:
Fernandez-Quilez, Alvaro, Nordström, Tobias, Jäderling, Fredrik, Kjosavik, Svein Reidar, Eklund, Martin
Background: Prostate cancer (PC) MRI-based risk calculators are commonly based on biological (e.g. PSA), MRI markers (e.g. volume), and patient age. Whilst patient age measures the amount of years an individual has existed, biological age (BA) might
Externí odkaz:
http://arxiv.org/abs/2308.05344