Dataset Open Access
2D and 3D convolutional neural networks for outcome modelling of locally advanced head and neck squamous cell carcinoma
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
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.
| Name | Size | |
|---|---|---|
|
analysis_output.zip
md5:6582c760d221af13f42e352eb8de92ce |
118.1 GB | Download |
| All versions | This version | |
|---|---|---|
| Views | 962 | 962 |
| Downloads | 327 | 327 |
| Data volume | 38.6 TB | 38.6 TB |
| Unique views | 577 | 577 |
| Unique downloads | 64 | 64 |
- Publication date:
- February 27, 2020
- DOI:
-
- Keyword(s):
- convolutional neural networks Keras Deep learning head and neck cancer loco-regional-recurrence Cox proportional hazards
- Related identifiers:
- Identical to:
https://www.hzdr.de/publications/Publ-30759 - Referenced by:
https://www.hzdr.de/publications/Publ-30750 - Communities:
- License (for files):
- Creative Commons Attribution Non Commercial 4.0 International