A comparative study of machine learning methods for time-to-event survival data for radiomics risk modelling

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A comparative study of machine learning methods for time-to-event survival data for radiomics risk modelling

Author: Leger, Stefan; Zwanenburg, Alex; Pilz, Karoline; Lohaus, Fabian; Linge, Annett; Zoephel, Klaus; Kotzerke, Joerg; Schreiber, Andreas; Tinhofer, Inge; Budach, Volker; Sak, Ali; Stuschke, Martin; Balermpas, Panagiotis; Roedel, Claus; Ganswindt, Ute; Belka, Claus; Pigorsch, Steffi; Combs, Stephanie E.; Moennich, David; Zips, Daniel; Krause, Mechthild; Baumann, Michael; Troost, Esther G. C.; Loeck, Steffen; Richter, Christian
Tübinger Autor(en):
Zips, Daniel
Mönnich, David
Published in: Scientific Reports (2017), Bd. 7, Article 13206
Verlagsangabe: Nature Publishing Group
Language: English
Full text: http://dx.doi.org/10.1038/s41598-017-13448-3
ISSN: 2045-2322
DDC Classifikation: 500 - Natural sciences and mathematics
Dokumentart: Artikel
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