A Machine-Learning-Based Drug Repurposing Approach Using Baseline Regularization. View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2019

AUTHORS

Zhaobin Kuang , Yujia Bao , James Thomson , Michael Caldwell , Peggy Peissig , Ron Stewart , Rebecca Willett , David Page

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. More... »

PAGES

255-267

References to SciGraph publications

  • 2001-06. Convergence of a Block Coordinate Descent Method for Nondifferentiable Minimization in JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/978-1-4939-8955-3_15

    DOI

    http://dx.doi.org/10.1007/978-1-4939-8955-3_15

    DIMENSIONS

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    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/30547447


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