A concrete implementation of the use case discussed in this chapter can be found here: https://github.com/PacktPublishing/Java-Deep-Learning-Cookbook/blob/master/06_Constructing_LSTM_Network_for_time_series/sourceCode/cookbookapp-lstm-time-series/src/main/java/LstmTimeSeriesExample.java.

After cloning the GitHub repository, navigate to the Java-Deep-Learning-Cookbook/06_Constructing_LSTM_Network_for_time_series/sourceCode directory. Then, import the cookbookapp-lstm-time-series project as a Maven project by importing pom.xml.

Download the clinical time series data from here: https://skymindacademy.blob.core.windows.net/physionet2012/physionet2012.tar.gz. The dataset is from the PhysioNet Cardiology Challenge 2012.

Unzip the package after the download. You should see the following directory structure:

The features are contained in a directory called sequence and the labels are contained in a directory called mortality. Ignore the other directories for now. You need to update file paths to features/labels in the source code to run the example.