Fuzzy measure of multiple risk factors in the prediction of osteoporotic fractures

  • Authors:
  • Tuan D. Pham;Miriam Brandl;Nguyen D. Nguyen;Tuan V. Nguyen

  • Affiliations:
  • James Cook University, Bioinformatics Applications Research Center, School of Mathematics, Physics and IT, Townsville, QLD, Australia;James Cook University, Bioinformatics Applications Research Center, School of Mathematics, Physics and IT, Townsville, QLD, Australia;Garvan Institute of Medical Research, Darlinghurst, NSW, Australia;Garvan Institute of Medical Research, Darlinghurst, NSW, Australia

  • Venue:
  • FS'08 Proceedings of the 9th WSEAS International Conference on Fuzzy Systems
  • Year:
  • 2008

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Abstract

Progress in the study of osteoporosis can only be made if its symptons can be diagnosed before bone fractures occur. However, osteoporotic fractures still remain unpredicted at large because the conditions leading to such fractures are due to multiple factors which are partially understood and incomplete. While the measurements of bone-mineral density (BMD) are primarily important in the evaluation and prediction of patients at risk of osteoporosis, patients' access to such measurements is not always feasible. This paper utilizes the theory of fuzzy measures to study the interactions of multiple fracture-risk factors. In a particular case study, we identified several subsets of risk factors that both have higher impact factors than those with the inclusion of BMD measurement and can be easily assessed by routine clinical practice. The results have shown a potential application of the fuzzy model for identifying the importance of the interactions of multiple risk factors being not associated with BMD measurements.