Machine Learning Approaches to Surrogate Multifidelity Growth and Remodeling Models for Efficient Abdominal Aortic Aneurysmal Applications

Documenti analoghi

• Computational Growth and Remodeling of Abdominal Aortic Aneurysms Constrained by the Spine
  di: Farsad, Mehdi, et al.
  Pubblicazione: (2015)
• Patient-Specific Prediction of Abdominal Aortic Aneurysm Expansion using Bayesian Calibration
  di: Zhang, Liangliang, et al.
  Pubblicazione: (2019)
• Prior Distributions of Material Parameters for Bayesian Calibration of Growth and Remodeling Computational Model of Abdominal Aortic Wall
  di: Seyedsalehi, Sajjad, et al.
  Pubblicazione: (2015)
• Current state-of-the-art and utilities of machine learning for detection, monitoring, growth prediction, rupture risk assessment, and post-surgical management of abdominal aortic aneurysms
  di: Seungik Baek, et al.
  Pubblicazione: (2022-06-01)
• Intraluminal thrombus effect on the progression of abdominal aortic aneurysms by using a multistate continuous-time Markov chain model
  di: Zhang, Liangliang, et al.
  Pubblicazione: (2020)