@misc{indiciaef9255a9d696a,
  title = {Personalized and uncertainty-aware coronary hemodynamics simulations: From Bayesian estimation to improved multi-fidelity uncertainty quantification},
  author = {Menon, Karthik [Georgia Institute of Technology, Atlanta, GA (United States)] (ORCID:0000000274947585) and Zanoni, Andrea [Stanford School of Medicine, Stanford, CA (United States); Stanford University, CA (United States)] (ORCID:000000027337288X) and Khan, M. Owais [Toronto Metropolitan University, ON (Canada)] (ORCID:0000000151371942) and Geraci, Gianluca [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)] and Nieman, Koen [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)] and Schiavazzi, Daniele E. [University of Notre Dame, IN (United States)] (ORCID:0000000192055989) and Marsden, Alison L. [Stanford School of Medicine, Stanford, CA (United States); Stanford University, CA (United States)]},
  year = {2025},
  doi = {10.1016/j.cmpb.2025.108951},
  url = {https://www.osti.gov/biblio/2585713},
  note = {Source identifier: 2585713}
}