TY - GEN
T1 - Patient monitoring and diagnosis assistance by integrating statistical and artificial intelligence tools
AU - Tatara, Eric
AU - Cinar, Ali
AU - DeCicco, Jeffrey
AU - Raj, Raghu
AU - Aggarwal, Neil
AU - Chesebro, Michelle
AU - Evans, Jennifer
AU - Shah-Khan, Miraj
AU - Zloza, Andrew
PY - 1999
Y1 - 1999
N2 - 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.
AB - 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.
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M3 - Conference contribution
AN - SCOPUS:0033350907
SN - 0780356756
T3 - Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
SP - 699
BT - Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
PB - IEEE
T2 - Proceedings 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)
Y2 - 13 October 1999 through 16 October 1999
ER -