Patient monitoring and diagnosis assistance by integrating statistical and artificial intelligence tools

Eric Tatara, Ali Cinar, Jeffrey DeCicco, Raghu Raj, Neil Aggarwal, Michelle Chesebro, Jennifer Evans, Miraj Shah-Khan, Andrew Zloza

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

Abstract

Patient monitoring by automated data collection has created new challenges for health care professionals in their efforts to extract useful information from raw data. New online monitoring devices may generate large amounts of data that must be interpreted quickly and accurately. The use of statistical methods and artificial intelligence tools to summarize and interpret high frequency physiologic data such as the electrocardiogram (EKG) are investigated. The development of a methodology and its associated tools for real-time patient data monitoring and diagnosis was accomplished by using the commercial programming environments MATLAB and G2, a real-time knowledge-based system (KBS) development shell. A KBS was developed that incorporates various statistical methods with a rule-based decision system to detect abnormal situations, provide preliminary interpretation and diagnosis, and to report these findings to the physician.

Original languageEnglish (US)
Title of host publicationAnnual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
PublisherIEEE
Pages699
Number of pages1
ISBN (Print)0780356756
StatePublished - 1999
Externally publishedYes
EventProceedings of the 1999 IEEE Engineering in Medicine and Biology 21st Annual Conference and the 1999 Fall Meeting of the Biomedical Engineering Society (1st Joint BMES / EMBS) - Atlanta, GA, USA
Duration: Oct 13 1999Oct 16 1999

Publication series

NameAnnual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
Volume2
ISSN (Print)0589-1019

Other

OtherProceedings of the 1999 IEEE Engineering in Medicine and Biology 21st Annual Conference and the 1999 Fall Meeting of the Biomedical Engineering Society (1st Joint BMES / EMBS)
CityAtlanta, GA, USA
Period10/13/9910/16/99

ASJC Scopus subject areas

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

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