Dataset Closed Access
Data publication: Multitask learning with convolutional neural networks and vision transformers can improve outcome prediction for head and neck cancer patients
Starke, Sebastian;
Zwanenburg, Alex;
Leger, Karoline;
Lohaus, Fabian;
Linge, Annett;
Schreiber, Andreas;
Kalinauskaite, Goda;
Tinhofer, Inge;
Guberina, Nika;
Guberina, Maja;
Balermpas, Panagiotis;
von der Grün, Jens;
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
This dataset contains the model checkpoints, predictions and performance metrics for the multitask neural networks presented in the corresponding manuscript.
Closed Access
Files are not publicly accessible.
998
12
views
downloads
| All versions | This version | |
|---|---|---|
| Views | 998 | 998 |
| Downloads | 12 | 12 |
| Data volume | 2.0 TB | 2.0 TB |
| Unique views | 948 | 948 |
| Unique downloads | 2 | 2 |
- Publication date:
- August 16, 2023
- DOI:
-
- Keyword(s):
- survival analysis vision transformer convolutional neural network multitask learning tumor segmentation head and neck cancer Cox proportional hazards loco-regional control progression-free survival discrete-time survival models
- Related identifiers:
- Identical to:
https://www.hzdr.de/publications/Publ-37408 - Referenced by:
10.3390/cancers15194897, https://www.hzdr.de/publications/Publ-37388, https://www.hzdr.de/publications/Publ-39339 - Communities: