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.

中文翻译：

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通过代表性的小波挖掘提高时间生物标志物发现中的统计能力

纵向数据中的时间生物标记发现是基于检测重复发生的轨迹，即所谓的shapelets。搜索shapelet需要考虑数据中的所有子序列。虽然在先前的工作中减轻了伴随的多次测试问题，但是检测到的小形的冗余和重叠导致先验无数个高度相似且在结构上无意义的小形。结果，当前的时间生物标志物发现方法不切实际并且功能不足。