A computational framework for search, discovery, and trending of patient health in radiology reports

Robert M. Patton, Carlos C. Rojas, Barbara G. Beckerman, Thomas E. Potok

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The healthcare industry as a whole lags far behind other industries in terms of knowledge discovery capabilities. There are many piece-wise approaches to analysis of patient records. Unfortunately, there are few approaches that enable a completely automated approach that supports not just search, but also discovery and prediction of patient health. The work presented here describes a computational framework that provides near complete automation of the discovery and trending of patient characteristics. This approach has been successfully applied to the domain of mammography, but could be applied to other domains of radiology with minimal effort.

Original languageEnglish
Title of host publicationProceedings - 2011 1st IEEE International Conference on Healthcare Informatics, Imaging and Systems Biology, HISB 2011
Pages104-111
Number of pages8
DOIs
StatePublished - 2011
Event2011 1st IEEE International Conference on Healthcare Informatics, Imaging and Systems Biology, HISB 2011 - San Jose, CA, United States
Duration: Jul 26 2011Jul 29 2011

Publication series

NameProceedings - 2011 1st IEEE International Conference on Healthcare Informatics, Imaging and Systems Biology, HISB 2011

Conference

Conference2011 1st IEEE International Conference on Healthcare Informatics, Imaging and Systems Biology, HISB 2011
Country/TerritoryUnited States
CitySan Jose, CA
Period07/26/1107/29/11

Keywords

  • genetic algorithm
  • information retrieval
  • radiology
  • wavelets

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