Zobrazeno 1 - 10
of 12 694
pro vyhledávání: '"Reader, A."'
Autor:
Chanda, Tirtha, Haggenmueller, Sarah, Bucher, Tabea-Clara, Holland-Letz, Tim, Kittler, Harald, Tschandl, Philipp, Heppt, Markus V., Berking, Carola, Utikal, Jochen S., Schilling, Bastian, Buerger, Claudia, Navarrete-Dechent, Cristian, Goebeler, Matthias, Kather, Jakob Nikolas, Schneider, Carolin V., Durani, Benjamin, Durani, Hendrike, Jansen, Martin, Wacker, Juliane, Wacker, Joerg, Consortium, Reader Study, Brinker, Titus J.
Artificial intelligence (AI) systems have substantially improved dermatologists' diagnostic accuracy for melanoma, with explainable AI (XAI) systems further enhancing clinicians' confidence and trust in AI-driven decisions. Despite these advancements
Externí odkaz:
http://arxiv.org/abs/2409.13476
Autor:
Reader, Matthew
Experimental errors are now incredibly precise, and are often dominated by the systematic uncertainties. Therefore the errors obtained in the Parton Distribution Functions that are extracted from this data will also be dominated by these experimental
Externí odkaz:
http://arxiv.org/abs/2408.12922
Autor:
Reader, Callum
It is known that every monoidal bicategory has an associated braided monoidal category of scalars. In this thesis we show that every monoidal bicategory, which is closed both monoidally and compositionally, can be enriched over the monoidal 2-categor
Externí odkaz:
http://arxiv.org/abs/2403.14475
Echocardiography (echo) is the first imaging modality used when assessing cardiac function. The measurement of functional biomarkers from echo relies upon the segmentation of cardiac structures and deep learning models have been proposed to automate
Externí odkaz:
http://arxiv.org/abs/2403.07818
Autor:
Mariska Naude, Ashleigh van Heerden, Janette Reader, Mariëtte van der Watt, Jandeli Niemand, Dorè Joubert, Giulia Siciliano, Pietro Alano, Mathew Njoroge, Kelly Chibale, Esperanza Herreros, Didier Leroy, Lyn-Marié Birkholtz
Publikováno v:
Nature Communications, Vol 15, Iss 1, Pp 1-15 (2024)
Abstract Novel antimalarial compounds targeting both the pathogenic and transmissible stages of the human malaria parasite, Plasmodium falciparum, would greatly benefit malaria elimination strategies. However, most compounds affecting asexual blood s
Externí odkaz:
https://doaj.org/article/8064c37c106b46e4a45b831578d96156
Publikováno v:
EJNMMI Physics, Vol 11, Iss 1, Pp 1-24 (2024)
Abstract Background Multiplexed positron emission tomography (mPET) imaging can measure physiological and pathological information from different tracers simultaneously in a single scan. Separation of the multiplexed PET signals within a single PET s
Externí odkaz:
https://doaj.org/article/3b1fab1654bb4fa79d49ca88c63847c8
Autor:
Reader, Andrew J.
A unified self-supervised and supervised deep learning framework for PET image reconstruction is presented, including deep-learned filtered backprojection (DL-FBP) for sinograms, deep-learned backproject then filter (DL-BPF) for backprojected images,
Externí odkaz:
http://arxiv.org/abs/2302.13086
Autor:
Jessica Wimberly, Aleah Nguyen, Erica Memoli, Matt Kasman, Bill Heerman, Russell Pate, Evan Sommer, Adam Sedlak, Lydia Reader, Ross A. Hammond, Shari Barkin
Publikováno v:
Frontiers in Pediatrics, Vol 12 (2024)
Childhood physical activity sets the foundation for health. While we know many factors that contribute to physical activity, there are limitations in our knowledge, especially in early childhood. Through our review, we identify gaps in existing datas
Externí odkaz:
https://doaj.org/article/0f5a5a3e508945e0983075589826c418
Publikováno v:
Ecosphere, Vol 15, Iss 10, Pp n/a-n/a (2024)
Abstract Navigating social‐ecological systems toward sustainable trajectories is an important challenge of the Anthropocene. Models of social‐ecological systems can increase our understanding of how social and ecological subsystems interact, thei
Externí odkaz:
https://doaj.org/article/f0e13c1b789948ae817d1cd5e2ee3ded
Autor:
Tirtha Chanda, Katja Hauser, Sarah Hobelsberger, Tabea-Clara Bucher, Carina Nogueira Garcia, Christoph Wies, Harald Kittler, Philipp Tschandl, Cristian Navarrete-Dechent, Sebastian Podlipnik, Emmanouil Chousakos, Iva Crnaric, Jovana Majstorovic, Linda Alhajwan, Tanya Foreman, Sandra Peternel, Sergei Sarap, İrem Özdemir, Raymond L. Barnhill, Mar Llamas-Velasco, Gabriela Poch, Sören Korsing, Wiebke Sondermann, Frank Friedrich Gellrich, Markus V. Heppt, Michael Erdmann, Sebastian Haferkamp, Konstantin Drexler, Matthias Goebeler, Bastian Schilling, Jochen S. Utikal, Kamran Ghoreschi, Stefan Fröhling, Eva Krieghoff-Henning, Reader Study Consortium, Titus J. Brinker
Publikováno v:
Nature Communications, Vol 15, Iss 1, Pp 1-17 (2024)
Abstract Artificial intelligence (AI) systems have been shown to help dermatologists diagnose melanoma more accurately, however they lack transparency, hindering user acceptance. Explainable AI (XAI) methods can help to increase transparency, yet oft
Externí odkaz:
https://doaj.org/article/a7c398cf0b3b4b35ad5fc17b7f22b907