Zobrazeno 1 - 10
of 1 603
pro vyhledávání: '"Schwen, A"'
Autor:
Zerbe, Norman, Schwen, Lars Ole, Geißler, Christian, Wiesemann, Katja, Bisson, Tom, Boor, Peter, Carvalho, Rita, Franz, Michael, Jansen, Christoph, Kiehl, Tim-Rasmus, Lindequist, Björn, Pohlan, Nora Charlotte, Schmell, Sarah, Strohmenger, Klaus, Zakrzewski, Falk, Plass, Markus, Takla, Michael, Küster, Tobias, Homeyer, André, Hufnagl, Peter
Publikováno v:
Journal of Pathology Informatics 2024
Over the past decade, artificial intelligence (AI) methods in pathology have advanced substantially. However, integration into routine clinical practice has been slow due to numerous challenges, including technical and regulatory hurdles in translati
Externí odkaz:
http://arxiv.org/abs/2401.09450
Pathology laboratories are increasingly using digital workflows. This has the potential of increasing lab efficiency, but the digitization process also involves major challenges. Several reports have been published describing the individual experienc
Externí odkaz:
http://arxiv.org/abs/2306.03619
Autor:
Natalie Busby, Sarah Newman-Norlund, Sara Sayers, Chris Rorden, Roger Newman-Norlund, Janina Wilmskoetter, Rebecca Roth, Sarah Wilson, Deena Schwen-Blackett, Sigfus Kristinsson, Alex Teghipco, Julius Fridriksson, Leonardo Bonilha
Publikováno v:
Communications Biology, Vol 7, Iss 1, Pp 1-12 (2024)
Abstract Premature brain aging is associated with poorer cognitive reserve and lower resilience to injury. When there are focal brain lesions, brain regions may age at different rates within the same individual. Therefore, we hypothesize that reduced
Externí odkaz:
https://doaj.org/article/8566612a90b4461496ff8b8bb48e070c
Publikováno v:
Computational Materials Science, 218, (2023) 111969
Engineering alloys generally exhibit multi-phase microstructures. For simulating their microstructure evolution during solid-state phase transformation, CALPHAD-guided multi-phase-field models coupled with micro-mechanics have proven to be a reliable
Externí odkaz:
http://arxiv.org/abs/2301.01747
Publikováno v:
International Journal of Solids and Structures, 250, (2022) 111709
This paper presents an efficient and quantitative phase-field model for elastically heterogeneous alloys that ensures the two mechanical compatibilities$\unicode{x2014}$static and kinematic, in conjunction with chemical equilibrium within the interfa
Externí odkaz:
http://arxiv.org/abs/2301.01746
Autor:
Norman Zerbe, Lars Ole Schwen, Christian Geißler, Katja Wiesemann, Tom Bisson, Peter Boor, Rita Carvalho, Michael Franz, Christoph Jansen, Tim-Rasmus Kiehl, Björn Lindequist, Nora Charlotte Pohlan, Sarah Schmell, Klaus Strohmenger, Falk Zakrzewski, Markus Plass, Michael Takla, Tobias Küster, André Homeyer, Peter Hufnagl
Publikováno v:
Journal of Pathology Informatics, Vol 15, Iss , Pp 100387- (2024)
Over the past decade, artificial intelligence (AI) methods in pathology have advanced substantially. However, integration into routine clinical practice has been slow due to numerous challenges, including technical and regulatory hurdles in translati
Externí odkaz:
https://doaj.org/article/224c25035ba642a39b737874f9152e0c
Autor:
Guillaume Giudicelli, Alexander Lindsay, Logan Harbour, Casey Icenhour, Mengnan Li, Joshua E. Hansel, Peter German, Patrick Behne, Oana Marin, Roy H. Stogner, Jason M. Miller, Daniel Schwen, Yaqi Wang, Lynn Munday, Sebastian Schunert, Benjamin W. Spencer, Dewen Yushu, Antonio Recuero, Zachary M. Prince, Max Nezdyur, Tianchen Hu, Yinbin Miao, Yeon Sang Jung, Christopher Matthews, April Novak, Brandon Langley, Timothy Truster, Nuno Nobre, Brian Alger, David Andrs, Fande Kong, Robert Carlsen, Andrew E. Slaughter, John W. Peterson, Derek Gaston, Cody Permann
Publikováno v:
SoftwareX, Vol 26, Iss , Pp 101690- (2024)
The development of MOOSE has kept accelerating since the last release, with over 2,100 pull requests merged over the last 30 months that involved nearly fifty contributors across close to a dozen institutions internationally. The growth in MOOSE's ca
Externí odkaz:
https://doaj.org/article/31a1c295bf0145adb263697dd638f00f
Autor:
Homeyer, André, Geißler, Christian, Schwen, Lars Ole, Zakrzewski, Falk, Evans, Theodore, Strohmenger, Klaus, Westphal, Max, Bülow, Roman David, Kargl, Michaela, Karjauv, Aray, Munné-Bertran, Isidre, Retzlaff, Carl Orge, Romero-López, Adrià, Sołtysiński, Tomasz, Plass, Markus, Carvalho, Rita, Steinbach, Peter, Lan, Yu-Chia, Bouteldja, Nassim, Haber, David, Rojas-Carulla, Mateo, Sadr, Alireza Vafaei, Kraft, Matthias, Krüger, Daniel, Fick, Rutger, Lang, Tobias, Boor, Peter, Müller, Heimo, Hufnagl, Peter, Zerbe, Norman
Publikováno v:
Mod Pathol (2022)
Artificial intelligence (AI) solutions that automatically extract information from digital histology images have shown great promise for improving pathological diagnosis. Prior to routine use, it is important to evaluate their predictive performance
Externí odkaz:
http://arxiv.org/abs/2204.14226
Autor:
Liarte, Danilo B., Thornton, Stephen J., Schwen, Eric, Cohen, Itai, Chowdhury, Debanjan, Sethna, James P.
Disordered viscoelastic materials are ubiquitous and exhibit fascinating invariant scaling properties. In a companion article, we have presented comprehensive new results for the critical behavior of the dynamic susceptibility of disordered elastic s
Externí odkaz:
http://arxiv.org/abs/2202.13933
Publikováno v:
Informatics in Medicine Unlocked 29 (2022) 100853
Image analysis tasks in computational pathology are commonly solved using convolutional neural networks (CNNs). The selection of a suitable CNN architecture and hyperparameters is usually done through exploratory iterative optimization, which is comp
Externí odkaz:
http://arxiv.org/abs/2112.03622