Zobrazeno 1 - 10
of 1 832
pro vyhledávání: '"A. Rannikko"'
Publikováno v:
European Urology Open Science, Vol 63, Iss , Pp S12-S13 (2024)
Externí odkaz:
https://doaj.org/article/eb9caf4979d14f47818f41290035f0b9
Publikováno v:
European Urology Open Science, Vol 63, Iss , Pp S14- (2024)
Externí odkaz:
https://doaj.org/article/8687ed3b32ad4983acc9a397d51c80c1
Publikováno v:
European Urology Open Science, Vol 63, Iss , Pp S6- (2024)
Externí odkaz:
https://doaj.org/article/54b9e438607b438c9b4adecc3b62c8c3
Autor:
H.B. Luiting, R. Valdagni, E.R. Boevé, F. Staerman, J. Rueb, A. Rannikko, A. Semjonow, M.J. Roobol
Publikováno v:
European Urology Open Science, Vol 21, Iss , Pp S88-S89 (2020)
Externí odkaz:
https://doaj.org/article/dedd2f9394d14f7b80b4dfc46fb1af8e
Autor:
R. Hietikko, T.P. Kilpeläinen, A. Kenttämies, J. Ronkainen, K. Ijäs, K. Lind, S. Marjasuo, J. Oksala, O. Oksanen, T. Saarinen, R. Savolainen, K. Taari, T.L.J. Tammela, T. Mirtti, K. Natunen, A. Auvinen, A. Rannikko
Publikováno v:
European Urology Open Science, Vol 19, Iss , Pp e166- (2020)
Externí odkaz:
https://doaj.org/article/058dce710c6448e1bc6b7b95b2bd36af
Publikováno v:
European Urology Open Science, Vol 19, Iss , Pp e1543-e1544 (2020)
Externí odkaz:
https://doaj.org/article/d42f2365a83446a2b5434a04d1e3ac6f
A first step towards a global nomogram to predict disease progression for men on active surveillance
Autor:
M. Van Hemelrijck, X. Ji, J. Helleman, M. Roobol, D. Nieboer, C. Bangma, M. Frydenberg, A. Rannikko, L-S. Lee, V. Gnanapragsam, M. Kattan
Publikováno v:
European Urology Open Science, Vol 19, Iss , Pp e1905-e1906 (2020)
Externí odkaz:
https://doaj.org/article/134642d58f254e4aa2e373c57e93af97
Publikováno v:
European Urology Open Science, Vol 19, Iss , Pp e2314- (2020)
Externí odkaz:
https://doaj.org/article/bcdf73fa09334589b5340e5a9edc01f5
Autor:
Batouche, Abderrahim Oussama, Czeizler, Eugen, Koskinen, Miika, Mirtti, Tuomas, Rannikko, Antti Sakari
The presence of detailed clinical information in electronic health record (EHR) systems presents promising prospects for enhancing patient care through automated retrieval techniques. Nevertheless, it is widely acknowledged that accessing data within
Externí odkaz:
http://arxiv.org/abs/2311.02086
Autor:
Pohjonen, Joona, Stürenberg, Carolin, Föhr, Atte, Randen-Brady, Reija, Luomala, Lassi, Lohi, Jouni, Pitkänen, Esa, Rannikko, Antti, Mirtti, Tuomas
Deep neural networks have achieved impressive performance in a wide variety of medical imaging tasks. However, these models often fail on data not used during training, such as data originating from a different medical centre. How to recognize models
Externí odkaz:
http://arxiv.org/abs/2206.15274