A statistical dynamics approach to the study of human health data: Resolving population scale diurnal variation in laboratory data
A statistical dynamics approach to the study of human health data: Resolving population scale diurnal variation in laboratory data
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DOI：
10.1016/j.physleta.2009.12.067
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发表时间：
2010-02-15
影响因子：
2.6
通讯作者：
Hripcsak, George
中科院分区：
文献类型：
--
作者：
Albers, D. J.;Hripcsak, George
将统计物理学和信息论应用于患者数据库中的临床化学测量，该数据库包含20年内250万患者的数据。尽管在所有时间内聚集所有患者（关于特定的临床化学测量）的看似幼稚的方法，但检测到时间延迟的互信息的衰减中的昼夜信号和具有不同健康状况的两个亚群的存在。这提供了一个原则上的证据，即电子健康记录中高度碎片化的数据在定义疾病和人类表型方面具有潜在的有用性。(C)出版社：Elsevier B.V.
Statistical physics and information theory is applied to the clinical chemistry measurements present in a patient database containing 2.5 million patients' data over a 20-year period. Despite the seemingly naive approach of aggregating all patients over all times (with respect to particular clinical chemistry measurements), both a diurnal signal in the decay of the time-delayed mutual information and the presence of two sub-populations with differing health are detected. This provides a proof in principle that the highly fragmented data in electronic health records has potential for being useful in defining disease and human phenotypes. (C) 2010 Published by Elsevier B.V.