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.
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| All versions | This version | |
|---|---|---|
| Views | 892 | 892 |
| Downloads | 12 | 12 |
| Data volume | 2.0 TB | 2.0 TB |
| Unique views | 842 | 842 |
| 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: