Information theory characteristics improve the prediction of lithium response in bipolar disorder patients using a Support Vector Machine classifier.

The addition of Information theory-derived features provides further knowledge about the distribution of the parameters and their interactions, thus significantly improving the ability to discriminate and predict the LRs from the NRs and the patients from the controls.