A Comparative Study of Bayes Net, Naive Bayes and Averaged One-Dependence Estimators for Osteoporosis Analysis.

Journal: Studies in health technology and informatics
Published Date: Jan 1, 2015

Abstract

This paper presents an evaluation of the accuracy of the Bayesian classifiers: Bayes Net, Naive Bayes and Averaged One-Dependence Estimator, to support diagnoses of osteopenia and osteoporosis. All classifiers showed good results, thus, given data, it is possible to produce a reasonably accurate estimate of the diagnosis.

Authors

  • Priscyla Waleska Simões
    Research Group in Information and Communications Technology in Health, UNESC, Criciúma, SC, Brazil.
  • Leandro Luiz Mazzuchello
    Research Group in Information and Communications Technology in Health, UNESC, Criciúma, SC, Brazil.
  • Larissa Letieli Toniazzo de Abreu
    Research Group in Information and Communications Technology in Health, UNESC, Criciúma, SC, Brazil.
  • Diego Garcia
    Research Group in Information and Communications Technology in Health, UNESC, Criciúma, SC, Brazil.
  • Maitê Gabriel dos Passos
    Research Group in Information and Communications Technology in Health, UNESC, Criciúma, SC, Brazil.
  • Ramon Venson
    Research Group in Information and Communications Technology in Health, UNESC, Criciúma, SC, Brazil.
  • Luciane Bisognin Ceretta
    Postgraduate Program in Public Health, UNESC, Criciúma, SC, Brazil.
  • Ana Carolina Veiga Silva
    Research Group in Information and Communications Technology in Health, UNESC, Criciúma, SC, Brazil.
  • Maria Inês da Rosa
    Postgraduate Program in Public Health, UNESC, Criciúma, SC, Brazil.
  • Paulo João Martins
    Postgraduate Program in Health Technology, Pontifícia Universidade Católica do Paraná, Curitiba, PR, Brazil.

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