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Interpretable and continuous AKI prediction in the intensive care

License: GNU General Public License v3.0

Jupyter Notebook 100.00%
clinical-prediction-models lstm-neural-networks machine-learning time-series

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continuous-aki-predict's Issues

Feature size is not the same after padding for train and test data

Hello @mapo89,

I am trying to reproduce the results in the paper using MIMIC-III v1.4. However, I am stuck at a point while training the LR model - the size of the features are not identical for training and test set. Please see the snapshot below:

image

image

  1. Could you kindly suggest what could have gone wrong; I did not change anything in the code except minor changes for the version like append to _append etc.

  2. Also, by any chance, would you have the jupyter-notebook with result for every block?

Thanks.

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