Patient-like-mine: A real time, visual analytics tool for clinical decision support

Peter Li, Simon N. Yates, Jenna K. Lovely, David Larson

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

We developed a real-time, visual analytics tool for clinical decision support. The system expands the «recall of past experience» approach that a provider (physician) uses to formulate a course of action for a given patient. By utilizing Big-Data techniques, we enable the provider to recall all similar patients from an institution's electronic medical record (EMR) repository, to explore «what-if» scenarios, and to collect these evidence-based cohorts for future statistical validation and pattern mining.

Original languageEnglish (US)
Title of host publicationProceedings - 2015 IEEE International Conference on Big Data, IEEE Big Data 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2865-2867
Number of pages3
ISBN (Electronic)9781479999255
DOIs
StatePublished - Dec 22 2015
Event3rd IEEE International Conference on Big Data, IEEE Big Data 2015 - Santa Clara, United States
Duration: Oct 29 2015Nov 1 2015

Other

Other3rd IEEE International Conference on Big Data, IEEE Big Data 2015
CountryUnited States
CitySanta Clara
Period10/29/1511/1/15

Keywords

  • clinical decision support
  • data mining
  • electronic medical record
  • real-time analytics
  • visual analytics

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Computer Science Applications
  • Information Systems
  • Software

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    Li, P., Yates, S. N., Lovely, J. K., & Larson, D. (2015). Patient-like-mine: A real time, visual analytics tool for clinical decision support. In Proceedings - 2015 IEEE International Conference on Big Data, IEEE Big Data 2015 (pp. 2865-2867). [7364104] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/BigData.2015.7364104