| Literature DB >> 30547447 |
Zhaobin Kuang1, Yujia Bao2, James Thomson3, Michael Caldwell4, Peggy Peissig4, Ron Stewart3, Rebecca Willett5, David Page5.
Abstract
We present the baseline regularization model for computational drug repurposing using electronic health records (EHRs). In EHRs, drug prescriptions of various drugs are recorded throughout time for various patients. In the same time, numeric physical measurements (e.g., fasting blood glucose level) are also recorded. Baseline regularization uses statistical relationships between the occurrences of prescriptions of some particular drugs and the increase or the decrease in the values of some particular numeric physical measurements to identify potential repurposing opportunities.Entities:
Keywords: Computational drug repurposing; Electronic health records; Longitudinal data; Self-controlled case series; Silico repurposing
Mesh:
Year: 2019 PMID: 30547447 PMCID: PMC6296259 DOI: 10.1007/978-1-4939-8955-3_15
Source DB: PubMed Journal: Methods Mol Biol ISSN: 1064-3745