Comments (1)
Thx for your feedback.
TFDeepSurv cannot directly be utilized for medical iamges. It is developed for a feature representation. If you want to use this package on your own images, maybe you can try to
- add some conv modules in the model to extract the feature of image;
- firstly obtain representations of images and then input it to TFDeepSurv.
Any survival prediction related models can be built upon TFDeepSurv. All you need is to deal with the input data (tables, images or 3D objects).
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Related Issues (17)
- How to test this with a new data set sample? HOT 17
- why `batch` is not appropriate in survival analysis? HOT 2
- Demonstration data error HOT 1
- Activation functions for hpopt.py
- loss diverges to NaN HOT 1
- The Average loss at step remains unchanged HOT 1
- The NAN value appears when used Bayesian Hyperparameters Optimization
- Why the parameters optimized by Bayesian parameters are not optimal? HOT 1
- Is there any relevant literature? HOT 1
- How to save the model? HOT 2
- Hyper parameter search with real data set - a concern on CI values... HOT 2
- What are the complete names of these algorithms ("wwe", "kp", "bsl", "Breslow" , "Efron" )? HOT 1
- hyptop issues HOT 8
- TypeError: Object of type int32 is not JSON serializable HOT 1
- Cannot restore variables (weights and bias) HOT 2
- gpu support HOT 2
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