Visual analytics to optimize patient-population evidence delivery for personalized care

Conference Paper

Electronic medical records (EMR) can be used to identify cohorts of patients who are clinically comparable to an individual patient. In this paper, we describe an approach that applies visual analytics to EMR data to describe the clinical course for an individual patient, display outcomes for a comparable cohort stratified by treatment, and generate predictions regarding a patient's clinical course based on treatment options. The visual display of information is designed to help clinicians choose among alternative therapies based on the EMR-derived outcomes of the cohort. Copyright © 2007 by the Association for Computing Machinery.

Full Text

Duke Authors

Cited Authors

  • Mane, KK; Owen, P; Schmitt, C; Wilhelmsen, K; Gersing, K; Pietrobon, R; Akushevich, I

Published Date

  • November 28, 2013

Published In

  • 2013 ACM Conference on Bioinformatics, Computational Biology and Biomedical Informatics, ACM-BCB 2013

Start / End Page

  • 484 - 488

International Standard Book Number 13 (ISBN-13)

  • 9781450324342

Digital Object Identifier (DOI)

  • 10.1145/2506583.2506608

Citation Source

  • Scopus