2D and 3D convolutional neural networks for outcome modelling of locally advanced head and neck squamous cell carcinoma

Dataset

DOI

These are the results from the analyses presented in a paper submitted to Scientific Reports.

The zip file contains the trained model files and the plots that were used in the manuscript.

Code for reproduction of our analyses can be obtained from https://github.com/oncoray/cnn-hnscc. There, you also find instructions on how to load our models.

Identifier
DOI	https://doi.org/10.14278/rodare.255
Related Identifier	https://www.hzdr.de/publications/Publ-30759
Related Identifier	https://www.hzdr.de/publications/Publ-30750
Related Identifier	https://doi.org/10.14278/rodare.254
Related Identifier	https://rodare.hzdr.de/communities/health
Related Identifier	https://rodare.hzdr.de/communities/rodare
Metadata Access	https://rodare.hzdr.de/oai2d?verb=GetRecord&metadataPrefix=oai_datacite&identifier=oai:rodare.hzdr.de:255

Provenance
Creator	Starke, Sebastian; Leger, Stefan; Zwanenburg, Alex; Leger, Karoline; Lohaus, Fabian; Linge, Annett; Schreiber, Andreas; Kalinauskaite, Goda; Tinhofer, Inge; Guberina, Nika; Guberina, Maja; Balermpas, Panagiotis; Grün, Jens von der; Ganswindt, Ute; Belka, Claus; Peeken, Jan C.; Combs, Stephanie E.; Böke, Simon; Zips, Daniel; Richter, Christian ; Troost, Esther Gera Cornelia ; Krause, Mechthild ; Baumann, Michael; Löck, Steffen
Publisher	Rodare
Publication Year	2020
Rights	Creative Commons Attribution Non Commercial 4.0 International; Open Access; https://creativecommons.org/licenses/by-nc/4.0/legalcode; info:eu-repo/semantics/openAccess
OpenAccess	true
Contact	https://rodare.hzdr.de/support

Representation
Resource Type	Dataset
Discipline	Life Sciences; Natural Sciences; Engineering Sciences