Enhancing statistical power in temporal biomarker discovery through representative shapelet mining

Thomas Gumbsch, Christian Bock, Michael Moor, Bastian Rieck, Karsten M. Borgwardt

Abstract: Temporal biomarker discovery in longitudinal data is based on detecting reoccurring trajectories, the so-called shapelets. The search for shapelets requires considering all subsequences in the data. While the accompanying issue of multiple testing has been mitigated in previous work, the redundancy and overlap of the detected shapelets results in an a priori unbounded number of highly similar and structurally meaningless shapelets. As a consequence, current temporal biomarker discovery methods are impractical and underpowered.