• DocumentCode
    227036
  • Title

    Fuzzy chest pain assessment for unstable angina based on Braunwald symptomatic and obesity clinical conditions

  • Author

    Orsi, Thiago ; Araujo, Ernesto ; Simoes, Ricardo

  • Author_Institution
    Fac. de Cienc. Med. de Minas Gerais (FCMMG), Belo Horizonte, Brazil
  • fYear
    2014
  • fDate
    6-11 July 2014
  • Firstpage
    1076
  • Lastpage
    1082
  • Abstract
    A fuzzy medical diagnostic decision system for helping support to evaluate patients with anginal chest pain and obesity clinical condition is proposed in this paper. Such an approach is based on the Braunwald symptomatic classification, the fuzzy set theory and fuzzy logic, and a risk obesity factor determined by a simplified Fuzzy Body Mass Index (FBMI). The fuzzy Braunwald symptomatic classification intertwined with the fuzzy obesity risk factor overwhelm the current rapid access chest pain clinic approaches that do not discriminate the obesity comorbidity or takes into account the subjectiveness, uncertainty, imprecision, and vagueness concerning such a clinical health condition. The resulting fuzzy obesity-based Braunwald symptomatic chest pain assessment is an alternative to support healthcare professionals in primary health care for patients with anginal chest pain worsened by the obesity clinical condition.
  • Keywords
    fuzzy logic; fuzzy set theory; health care; medical diagnostic computing; pattern classification; Braunwald symptomatic condition; FBMI; anginal chest pain; chest pain clinic approach; clinical health condition; fuzzy Braunwald symptomatic classification; fuzzy body mass index; fuzzy logic; fuzzy medical diagnostic decision system; fuzzy obesity risk factor; fuzzy obesity-based Braunwald symptomatic chest pain assessment; fuzzy set theory; healthcare professionals; obesity clinical conditions; primary health care; unstable angina; Indexes; Input variables; Medical diagnostic imaging; Obesity; Pain;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Systems (FUZZ-IEEE), 2014 IEEE International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    978-1-4799-2073-0
  • Type

    conf

  • DOI
    10.1109/FUZZ-IEEE.2014.6891836
  • Filename
    6891836