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pro vyhledávání: '"Siegemund, A"'
Autor:
Siegemund, Axel
Publikováno v:
Teocomunicação, Vol 53, Iss 1, p ID44005 (2023)
Cidadãos ambientalmente conscientes não pensam homogêneos. Suas diferentes percepções do mundo causam uma diversidade moral na política climática. O artigo mostra que as abordagens religiosas e não religiosas à adaptação climática remetem
Externí odkaz:
https://doaj.org/article/74d95f19a0c34944bc27695d4555d639
Autor:
Sereina Roffler, Hannah Büchler-Fehlberg, Anna Dietz, Rita Achermann, Markus Aschwanden, Daniel Staub, Caroline Kiss, Michael Dickenmann, Caroline Eva Gebhard, Alexa Hollinger, Martin Siegemund
Publikováno v:
Renal Replacement Therapy, Vol 10, Iss 1, Pp 1-11 (2024)
Abstract Background/objectives Shock and accompanying acute kidney injury (AKI) as a frequent complication is a well-known cause of morbidity and mortality worldwide. The current standard parameters to guide fluid resuscitation therapy (i.e., cardiac
Externí odkaz:
https://doaj.org/article/ad311701145344c9b4acc905ab9e3650
Autor:
Christian Pfrepper MD, Careen Franke MD, Michael Metze MD, Maria Weise MD, Annelie Siegemund PhD, Roland Siegemund PhD, Martin Federbusch MD, Reinhard Henschler MD, Sirak Petros MD, Manuela Konert MD
Publikováno v:
Clinical and Applied Thrombosis/Hemostasis, Vol 30 (2024)
The Total Thrombus-formation Analysis System (T-TAS) is an automated device using coated microchips to assess thrombus formation under flow conditions. Its value to monitor coagulation function in patients under antiplatelet therapy awaits further cl
Externí odkaz:
https://doaj.org/article/e2e81f5887f14b8fa94a3733e0194ed6
In this work, we introduce a novel Deep Learning-based method to perceive the environment of a vehicle based on radar scans while accounting for uncertainties in its predictions. The environment of the host vehicle is segmented into equally sized gri
Externí odkaz:
http://arxiv.org/abs/2306.03018
Towards a safe and comfortable driving, road scene segmentation is a rudimentary problem in camera-based advance driver assistance systems (ADAS). Despite of the great achievement of Convolutional Neural Networks (CNN) for semantic segmentation task,
Externí odkaz:
http://arxiv.org/abs/2207.02844
Autor:
Filippidis, Paraskevas, Hovius, Leana, Tissot, Frederic, Orasch, Christina, Flückiger, Ursula, Siegemund, Martin, Pagani, Jean-Luc, Eggimann, Philippe, Marchetti, Oscar, Lamoth, Frederic
Publikováno v:
In Journal of Critical Care August 2024 82
Autor:
Pfrepper, Christian, Koch, Elisabeth, Weise, Maria, Siegemund, Roland, Siegemund, Annelie, Petros, Sirak, Metze, Michael
Publikováno v:
In Research and Practice in Thrombosis and Haemostasis February 2023 7(2)
Akademický článek
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Autor:
van den Berg, Jana, Haslbauer, Jasmin D., Stalder, Anna K., Romanens, Anna, Mertz, Kirsten D., Studt, Jan-Dirk, Siegemund, Martin, Buser, Andreas, Holbro, Andreas, Tzankov, Alexandar
Publikováno v:
In Research and Practice in Thrombosis and Haemostasis May 2023 7(4)
Autor:
Manja Deforth, Caroline E. Gebhard, Susan Bengs, Philipp K. Buehler, Reto A. Schuepbach, Annelies S. Zinkernagel, Silvio D. Brugger, Claudio T. Acevedo, Dimitri Patriki, Benedikt Wiggli, Raphael Twerenbold, Gabriela M. Kuster, Hans Pargger, Joerg C. Schefold, Thibaud Spinetti, Pedro D. Wendel-Garcia, Daniel A. Hofmaenner, Bianca Gysi, Martin Siegemund, Georg Heinze, Vera Regitz-Zagrosek, Catherine Gebhard, Ulrike Held
Publikováno v:
Diagnostic and Prognostic Research, Vol 6, Iss 1, Pp 1-11 (2022)
Abstract Background The coronavirus disease 2019 (COVID-19) pandemic demands reliable prognostic models for estimating the risk of long COVID. We developed and validated a prediction model to estimate the probability of known common long COVID sympto
Externí odkaz:
https://doaj.org/article/683c9ba713cb425b8c158e6f5bb2b80c