Journal
PHYSICS LETTERS A
Volume 374, Issue 9, Pages 1159-1164Publisher
ELSEVIER
DOI: 10.1016/j.physleta.2009.12.067
Keywords
Time-delay dynamics; High-dimensional dynamics; Electronic health records; Information theory; Statistical mechanics; Clinical chemistry; Diurnal variation; Information theory; Mutual information
Categories
Funding
- NLM [RO1 LM06910]
- Microsoft Research for the Phenotypic Pipeline for Genome-wide Association Studies
- Smart Family Foundation
Ask authors/readers for more resources
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.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available