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Sensitivity analysis of the mechanical properties on atherosclerotic arteries rupture risk with an artificial neural network method.

Di ZuoDaye ChenMingji ZhuQiwen Xue
Published in: Computer methods in biomechanics and biomedical engineering (2024)
Considering the differences between individuals, in this paper, an uncertainty analysis model for predicting rupture risk of atherosclerotic arteries is established based on a back-propagation artificial neural network. The influence of isotropy and anisotropy on the rupture risk of atherosclerotic arteries is analyzed, and the results demonstrate the effectiveness of the artificial neural network in predicting the rupture risk. Moreover, the rupture risk of atherosclerotic arteries at different inflation sizes are simulated. This study contributes to a better understanding of the underlying mechanisms of atherosclerotic arteries rupture and promotes the advancement of artificial neural networks in atherosclerosis research.
Keyphrases
  • neural network
  • blood flow
  • randomized controlled trial
  • systematic review
  • cardiovascular disease
  • type diabetes