• DocumentCode
    561931
  • Title

    Comparison between man and machine in the case of acute coronary syndrome and acute myocardial infarction detection in a chest pain cohort in the emergency department

  • Author

    Abächerli, R. ; Leber, R. ; Christov, I. ; Twerenbold, R. ; Reichlin, T. ; Müller, C.

  • Author_Institution
    Biomed Res. & Signal Process., Schiller AG, Baar, Switzerland
  • fYear
    2011
  • fDate
    18-21 Sept. 2011
  • Firstpage
    777
  • Lastpage
    779
  • Abstract
    Acute myocardial infarction is a major cause of death and disability. Its rapid and reliable diagnosis is a major clinical need. The electrocardiogram and the measurement of myocardial enzymes are among others two important diagnostic methodologies to decide further management of chest pain patient after their presentation at the emergency department each having its strengths and drawbacks (e.g. detection accuracy versus time needed until possible decision). We wanted to know if it is with today´s current technology possible to replace the human decision blinded to clinical information after the patient´s initial presentation at the emergency department by an automatic diagnosis only based on one single electrocardiogram. We compared both decision results against an independent reference based on all clinically acquired parameters including a patient follow-up.
  • Keywords
    electrocardiography; enzymes; medical signal processing; patient diagnosis; acute coronary syndrome; acute myocardial infarction detection; automatic diagnosis; chest pain cohort; chest pain patient management; death; disability; electrocardiogram; emergency department; myocardial enzyme measurement; Algorithm design and analysis; Electrocardiography; Guidelines; Myocardium; Pain; Sensitivity; Training;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computing in Cardiology, 2011
  • Conference_Location
    Hangzhou
  • ISSN
    0276-6547
  • Print_ISBN
    978-1-4577-0612-7
  • Type

    conf

  • Filename
    6164681