Development of a vital sign data mining system for chronic patient monitoring

S. Tseng, Lee Cheng Chen, Chao Hui Lee, Jin Shang Wu, Yu Chia Hsu

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

13 Scopus citations

Abstract

In recent years, the structure of global population keeps going towards highly-aged continuously. The development of chronic patient medical care system becomes important and meaningful since people paid a lot attention to medical prevention. The medical care system has to provide alerts in time before the severe chronic illness occurs, such as stroke, diabetics, heart disease. Thus, necessary procedures can be taken in short time to save one precious life. In this paper, we presented a data mining system for chronic patient monitoring with applications on caring of cardiovascular patients. By mining vital signs like ECG the system can predict with a classification tree and inform doctors to take actions if any anomaly could happen. A series of experiments on PAF data showed that our system can stably predict the anomaly from patients' ECG data without coding of medical rules as done in other existing approaches.

Original languageEnglish
Title of host publicationProceedings - CISIS 2008
Subtitle of host publication2nd International Conference on Complex, Intelligent and Software Intensive Systems
Pages649-654
Number of pages6
DOIs
StatePublished - 8 Oct 2008
EventCISIS 2008: 2nd International Conference on Complex, Intelligent and Software Intensive Systems - Barcelona, Spain
Duration: 4 Mar 20087 Mar 2008

Publication series

NameProceedings - CISIS 2008: 2nd International Conference on Complex, Intelligent and Software Intensive Systems

Conference

ConferenceCISIS 2008: 2nd International Conference on Complex, Intelligent and Software Intensive Systems
CountrySpain
CityBarcelona
Period4/03/087/03/08

Keywords

  • Data mining
  • Electrocardiogram analysis
  • Patient monitoring system
  • Vital sign analysis

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