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pro vyhledávání: '"Kahmann, Jannik"'
Autor:
Dar, Salman Ul Hassan, Seyfarth, Marvin, Kahmann, Jannik, Ayx, Isabelle, Papavassiliu, Theano, Schoenberg, Stefan O., Frey, Norbert, Baeßler, Bettina, Foersch, Sebastian, Truhn, Daniel, Kather, Jakob Nikolas, Engelhardt, Sandy
AI models present a wide range of applications in the field of medicine. However, achieving optimal performance requires access to extensive healthcare data, which is often not readily available. Furthermore, the imperative to preserve patient privac
Externí odkaz:
http://arxiv.org/abs/2402.01054
Autor:
Dar, Salman Ul Hassan, Ghanaat, Arman, Kahmann, Jannik, Ayx, Isabelle, Papavassiliu, Theano, Schoenberg, Stefan O., Engelhardt, Sandy
Generative latent diffusion models have been established as state-of-the-art in data generation. One promising application is generation of realistic synthetic medical imaging data for open data sharing without compromising patient privacy. Despite t
Externí odkaz:
http://arxiv.org/abs/2307.01148
Autor:
Kahmann, Jannik1 (AUTHOR), Nörenberg, Dominik1 (AUTHOR), Papavassiliu, Theano2 (AUTHOR), Dar, Salman Ul Hassan3,4 (AUTHOR), Engelhardt, Sandy3,4 (AUTHOR), Schoenberg, Stefan O.1 (AUTHOR), Froelich, Matthias F.1 (AUTHOR), Ayx, Isabelle1 (AUTHOR) isabelle.ayx@medma.uni-heidelberg.de
Publikováno v:
Insights into Imaging. 7/6/2024, Vol. 15 Issue 1, p1-13. 13p.
Akademický článek
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