  The Temporal Group LASSO is an example of a multi-task, regularized
regression approach for the prediction of response variables that vary over
time. The aim of this work is to introduce the reader to the concepts behind
the Temporal Group LASSO and its related methods, as well as to the type of
potential applications in a healthcare setting that the method has. We argue
that the method is attractive because of its ability to reduce overfitting,
select predictors, learn smooth effect patterns over time, and finally, its
simplicity
