A machine learning approach for computation of cardiovascular intrinsic frequencies

• Rashid Alavi ,

  Contributed equally to this work with: Rashid Alavi, Qian Wang

  Roles Conceptualization, Formal analysis, Investigation, Methodology, Validation, Visualization, Writing – original draft

  Affiliation Department of Aerospace and Mechanical Engineering, University of Southern California, Los Angeles, California, United States of America

  https://orcid.org/0000-0003-1179-7089

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• Qian Wang ,

  Contributed equally to this work with: Rashid Alavi, Qian Wang

  Roles Formal analysis, Investigation, Methodology, Validation, Visualization, Writing – original draft

  Affiliation Beijing Computational Science Research Center, Beijing, China

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• Hossein Gorji,

  Roles Conceptualization, Methodology, Supervision, Writing – review & editing

  Affiliation Swiss Federal Laboratories for Materials Science and Technology (EMPA), Dubendorf, Switzerland

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• Niema M. Pahlevan

  Roles Conceptualization, Project administration, Supervision, Validation, Writing – review & editing

  * E-mail: pahlevan@usc.edu

  Affiliations Department of Aerospace and Mechanical Engineering, University of Southern California, Los Angeles, California, United States of America, Cardiovascular Research Institute, Huntington Medical Research Institutes, Pasadena, CA, United States of America, Division of Cardiovascular Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California, United States of America

  https://orcid.org/0000-0001-7498-0396

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