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Thank you for your creating the pycox. it's been really helpful to implement survival model for different datasets.
I am working on survival analysis for liver cancer patients. I am having 3D CT data and clinical data. I have been trying to implement "https://github.com/havakv/pycox/blob/master/examples/03_network_architectures.ipynb" for the 3D CT dataset. Is it possible to achieve this with the same structure. I want to use Autoencoder model for extracting the encoded features and then pass it to the LogisticHazard model. I need your help in knowing whether can this be done for the 3D CT dataset (instead of the tabular dataset) or not?
Thanking you
Nikhil kumar
The text was updated successfully, but these errors were encountered:
Hi Håvard Kvamme,
Thank you for your creating the pycox. it's been really helpful to implement survival model for different datasets.
I am working on survival analysis for liver cancer patients. I am having 3D CT data and clinical data. I have been trying to implement "https://github.com/havakv/pycox/blob/master/examples/03_network_architectures.ipynb" for the 3D CT dataset. Is it possible to achieve this with the same structure. I want to use Autoencoder model for extracting the encoded features and then pass it to the LogisticHazard model. I need your help in knowing whether can this be done for the 3D CT dataset (instead of the tabular dataset) or not?
Thanking you
Nikhil kumar
The text was updated successfully, but these errors were encountered: