Extracting and reading clinical data

ETL (short for Extract, Transform, and Load) is the most important step in any deep learning problem. We're focusing on data extraction in this recipe, where we will discuss how to extract and process clinical time series data. We have learned about regular data types, such as normal CSV/text data and images, in previous chapters. Now, let's discuss how to deal with time series data. We will use clinical time series data to predict the mortality of patients.

How to do it...

1. Create an instance of NumberedFileInputSplit to club all feature files together:

new NumberedFileInputSplit(FEATURE_DIR+"/%d.csv",0,3199);

2. Create an instance of NumberedFileInputSplit to club...