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Fracture prediction of cardiac lead medical devices using Bayesian networks

Author

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  • Haddad, Tarek
  • Himes, Adam
  • Campbell, Michael

Abstract

A novel Bayesian network methodology has been developed to enable the prediction of fatigue fracture of cardiac lead medical devices. The methodology integrates in-vivo device loading measurements, patient demographics, patient activity level, in-vitro fatigue strength measurements, and cumulative damage modeling techniques. Many plausible combinations of these variables can be simulated within a Bayesian network framework to generate a family of fatigue fracture survival curves, enabling sensitivity analyses and the construction of confidence bounds on reliability predictions.

Suggested Citation

  • Haddad, Tarek & Himes, Adam & Campbell, Michael, 2014. "Fracture prediction of cardiac lead medical devices using Bayesian networks," Reliability Engineering and System Safety, Elsevier, vol. 123(C), pages 145-157.
    • Handle: RePEc:eee:reensy:v:123:y:2014:i:c:p:145-157
    DOI: 10.1016/j.ress.2013.11.005
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    References listed on IDEAS

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    1. Stewart, Mark G. & O’Connor, Alan, 2012. "Probabilistic risk assessment and service life performance management of load bearing biomedical implants," Reliability Engineering and System Safety, Elsevier, vol. 108(C), pages 49-55.
    2. Marquez, David & Neil, Martin & Fenton, Norman, 2010. "Improved reliability modeling using Bayesian networks and dynamic discretization," Reliability Engineering and System Safety, Elsevier, vol. 95(4), pages 412-425.
    3. Langseth, Helge & Portinale, Luigi, 2007. "Bayesian networks in reliability," Reliability Engineering and System Safety, Elsevier, vol. 92(1), pages 92-108.
    4. AfDB AfDB, . "Annual Report 2012," Annual Report, African Development Bank, number 461.
    5. Peng, Weiwen & Huang, Hong-Zhong & Li, Yanfeng & Zuo, Ming J. & Xie, Min, 2013. "Life cycle reliability assessment of new products—A Bayesian model updating approach," Reliability Engineering and System Safety, Elsevier, vol. 112(C), pages 109-119.
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    Cited by:

    1. Hunte, Joshua L. & Neil, Martin & Fenton, Norman E., 2024. "A hybrid Bayesian network for medical device risk assessment and management," Reliability Engineering and System Safety, Elsevier, vol. 241(C).

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