论文标题
无视昼夜节律：英国生物库数据中的参与者遥测
Defying the Circadian Rhythm: Clustering Participant Telemetry in the UK Biobank Data
论文作者
论文摘要
英国生物银行数据集遵循超过500,000名志愿者，并包含与社会成果有关的各种信息。在这个庞大的收藏中，从腕上戴的加速度计收集的大量遥测提供了参与者活动的快照。使用这些数据，使用基于混合模型的方法分析了受到昼夜节律中断的转移工人的人群，以产生对生存结果的保护作用。在本文中，我们开发了一种可扩展，标准化且独特的方法，该方法有效地群集群集了大量的参与者遥测。通过建立Doherty等人的工作。 （2017年），我们引入了用于聚类目的的标准化，低维功能。使用基于矩阵变量混合模型的方法聚类参与者。一旦聚集，进行生存分析以证明每个集群中个体的不同寿命结果。总而言之，我们对英国生物银行参与者的一部分进行处理，聚类和分析，以显示出对昼夜节律中断个体的身体活动的保护作用。
The UK Biobank dataset follows over 500,000 volunteers and contains a diverse set of information related to societal outcomes. Among this vast collection, a large quantity of telemetry collected from wrist-worn accelerometers provides a snapshot of participant activity. Using this data, a population of shift workers, subjected to disrupted circadian rhythms, is analysed using a mixture model-based approach to yield protective effects from physical activity on survival outcomes. In this paper, we develop a scalable, standardized, and unique methodology that efficiently clusters a vast quantity of participant telemetry. By building upon the work of Doherty et al. (2017), we introduce a standardized, low-dimensional feature for clustering purposes. Participants are clustered using a matrix variate mixture model-based approach. Once clustered, survival analysis is performed to demonstrate distinct lifetime outcomes for individuals within each cluster. In summary, we process, cluster, and analyse a subset of UK Biobank participants to show the protective effects from physical activity on circadian disrupted individuals.
