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Python example prediction code for the PhysioNet/CinC Challenge 2019
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Example prediction code for Python for the PhysioNet/CinC Challenge 2019


This prediction code uses two scripts:

  • makes predictions on clinical time-series data. Add your prediction code to the get_sepsis_score function. To reduce your code's run time, add any code to the load_sepsis_model function that you only need to run once, such as loading weights for your model.
  • calls load_sepsis_model once and get_sepsis_score many times. It also performs all file input and output. Do not edit this script -- or we will be unable to evaluate your submission.

Check the code in these files for the input and output formats for the load_sepsis_model and get_sepsis_score functions.


You can run this prediction code by installing the NumPy package and running

python input_directory output_directory

where input_directory is a directory for input data files and output_directory is a directory for output prediction files. The PhysioNet/CinC 2019 webpage provides a training database with data files and a description of the contents and structure of these files.


See the PhysioNet/CinC 2019 webpage for more details, including instructions for the other files in this repository.

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