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CapSurv: Capsule Network for Survival Analysis With Whole Slide Pathological Images

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CapSurv

code for 《CapSurv: Capsule Network for Survival Analysis With Whole Slide Pathological Images》

Environment

python 2.7 Keras 2.1.4 tensorflow 1.5.0

GPU: 2*1080Ti

Data

train.npy: training data that must be ranked from long to short according to survival time

validation.npy: validation data

test.npy: test data

train_label.npy: the survival time of training data

validation_label.npy: the survival time of validation data

test_label.npy: the survival time of test data

train_label_onehot.npy: the one hot encoding of long or short term survivors of training data. The patients with no longer than 1-year survival are categorized as short term survivors labeled as 0, then the others as long term survivors labeled as 1

validation_label_onehot.npy: the one hot encoding of long or short term survivors of validation data

test_label_onehot.npy: the one hot encoding of long or short term survivors of test data

Usage

Use below instruction to run the code

python capsurv.py

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CapSurv: Capsule Network for Survival Analysis With Whole Slide Pathological Images

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