Zobrazeno 1 - 10
of 1 051
pro vyhledávání: '"Sampling strategies"'
Publikováno v:
Artificial Intelligence in Geosciences, Vol 5, Iss , Pp 100093- (2024)
Machine learning (ML) algorithms are frequently used in landslide susceptibility modeling. Different data handling strategies may generate variations in landslide susceptibility modeling, even when using the same ML algorithm. This research aims to c
Externí odkaz:
https://doaj.org/article/fae2a1952b294d0d8fd53fe5946c2c5f
Autor:
Žiga Tkalec, Jean-Philippe Antignac, Nicole Bandow, Frederic M. Béen, Lidia Belova, Jos Bessems, Bruno Le Bizec, Werner Brack, German Cano-Sancho, Jade Chaker, Adrian Covaci, Nicolas Creusot, Arthur David, Laurent Debrauwer, Gaud Dervilly, Radu Corneliu Duca, Valérie Fessard, Joan O. Grimalt, Thierry Guerin, Baninia Habchi, Helge Hecht, Juliane Hollender, Emilien L. Jamin, Jana Klánová, Tina Kosjek, Martin Krauss, Marja Lamoree, Gwenaelle Lavison-Bompard, Jeroen Meijer, Ruth Moeller, Hans Mol, Sophie Mompelat, An Van Nieuwenhuyse, Herbert Oberacher, Julien Parinet, Christof Van Poucke, Robert Roškar, Anne Togola, Jurij Trontelj, Elliott J. Price
Publikováno v:
Environment International, Vol 186, Iss , Pp 108585- (2024)
The chemical burden on the environment and human population is increasing. Consequently, regulatory risk assessment must keep pace to manage, reduce, and prevent adverse impacts on human and environmental health associated with hazardous chemicals. S
Externí odkaz:
https://doaj.org/article/a954656f71ff4863bc29976d595b4f42
Publikováno v:
Remote Sensing, Vol 16, Iss 2, p 320 (2024)
Due to the complex interaction of urban and mountainous floods, assessing flood susceptibility in mountainous urban areas presents a challenging task in environmental research and risk analysis. Data-driven machine learning methods can evaluate flood
Externí odkaz:
https://doaj.org/article/da0da4263e6a401297159d954c703899
Akademický článek
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Akademický článek
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Autor:
Somayeh Sadeghi, Davood Khalili, Azra Ramezankhani, Mohammad Ali Mansournia, Mahboubeh Parsaeian
Publikováno v:
BMC Medical Informatics and Decision Making, Vol 22, Iss 1, Pp 1-12 (2022)
Abstract Background Early detection and prediction of type two diabetes mellitus incidence by baseline measurements could reduce associated complications in the future. The low incidence rate of diabetes in comparison with non-diabetes makes accurate
Externí odkaz:
https://doaj.org/article/6595aff926744a74bba144cceb0d9d85
Autor:
Carla Galvez, Pía Boza, Mariluz González, Catalina Hormazabal, Marlene Encina, Manuel Azócar, Luis E. Castañeda, Angélica Rojo, María Luisa Ceballos, Paola Krall
Publikováno v:
Frontiers in Pharmacology, Vol 14 (2023)
Background: Kidney transplantation (KTx) requires immunosuppressive drugs such as Tacrolimus (TAC) which is mainly metabolized by CYP3A5. TAC is routinely monitored by trough levels (C0) although it has not shown to be a reliable marker. The area-und
Externí odkaz:
https://doaj.org/article/3c096cc401114927a90c3cd4f2278ec3
Akademický článek
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Publikováno v:
Applied Sciences, Vol 13, Iss 19, p 10667 (2023)
Object detection (OD) coupled with active learning (AL) has emerged as a powerful synergy in the field of computer vision, harnessing the capabilities of machine learning (ML) to automatically identify and perform image-based objects localisation whi
Externí odkaz:
https://doaj.org/article/24723a4139684237b7b78c2a4bc24a46
Autor:
Jamie S. Sanderlin, Jessie D. Golding, Taylor Wilcox, Daniel H. Mason, Kevin S. McKelvey, Dean E. Pearson, Michael K. Schwartz
Publikováno v:
BMC Public Health, Vol 21, Iss 1, Pp 1-10 (2021)
Abstract Background We evaluated whether occupancy modeling, an approach developed for detecting rare wildlife species, could overcome inherent accuracy limitations associated with rapid disease tests to generate fast, accurate, and affordable SARS-C
Externí odkaz:
https://doaj.org/article/a32ccfdf84b94f5e8be6e9539e307753