Literature DB >> 28921653

Visualization of temporal patterns in patient record data.

Catherine Plaisant1.   

Abstract

Visualization contributes to a variety of tasks, from reviewing individual patient records to helping researchers assess data quality, find patients of interest, review temporal patterns and anomalies, or understand differences between cohorts. We review some of visualization techniques developed at the University of Maryland.
© 2017 Société Française de Pharmacologie et de Thérapeutique.

Entities:  

Keywords:  data visualization; health patient record; temporal patterns

Mesh:

Year:  2017        PMID: 28921653      PMCID: PMC5771833          DOI: 10.1111/fcp.12322

Source DB:  PubMed          Journal:  Fundam Clin Pharmacol        ISSN: 0767-3981            Impact factor:   2.748


  3 in total

1.  Understanding Adherence and Prescription Patterns Using Large-Scale Claims Data.

Authors:  Margrét V Bjarnadóttir; Sana Malik; Eberechukwu Onukwugha; Tanisha Gooden; Catherine Plaisant
Journal:  Pharmacoeconomics       Date:  2016-02       Impact factor: 4.981

2.  Temporal event sequence simplification.

Authors:  Megan Monroe; Rongjian Lan; Hanseung Lee; Catherine Plaisant; Ben Shneiderman
Journal:  IEEE Trans Vis Comput Graph       Date:  2013-12       Impact factor: 4.579

3.  Coping with Volume and Variety in Temporal Event Sequences: Strategies for Sharpening Analytic Focus.

Authors:  Ben Shneiderman; Catherine Plaisant; Sana Malik; Adam Perer
Journal:  IEEE Trans Vis Comput Graph       Date:  2016-03-09       Impact factor: 4.579

  3 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.