Patents by Inventor Andrea Hawkins-Daarud

Andrea Hawkins-Daarud has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Methods for using machine learning and mechanistic models for biological feature mapping with multiparametric MRI
    Patent number: 11861475
    Abstract: Described here are systems and methods for generating and implementing a hybrid machine learning and mechanistic model to produce biological feature maps, or other measurements of biological features, based on an input of multiparametric magnetic resonance or other images. The hybrid model can include a combination of a machine learning model and a mechanistic model that takes as an input multiparametric MRI, or other imaging, data to generate biological feature maps (e.g., tumor cell density maps), or other measures or predictions of biological features (e.g., tumor cell density). The hybrid models have capabilities of learning individual-specific relationships between imaging features and biological features.
    Type: Grant
    Filed: November 19, 2018
    Date of Patent: January 2, 2024
    Assignees: Mayo Foundation for Medical Education and Research, Arizona Board of Regents on behalf of Arizona State University
    Inventors: Leland S. Hu, Jing Li, Kristin R. Swanson, Teresa Wu, Nathan Gaw, Hyunsoo Yoon, Andrea Hawkins-Daarud
  • Methods for Using Machine Learning and Mechanistic Models for Biological Feature Mapping with Multiparametric MRI
    Publication number: 20200342359
    Abstract: Described here are systems and methods for generating and implementing a hybrid machine learning and mechanistic model to produce biological feature maps, or other measurements of biological features, based on an input of multiparametric magnetic resonance or other images. The hybrid model can include a combination of a machine learning model and a mechanistic model that takes as an input multiparametric MRI, or other imaging, data to generate biological feature maps (e.g., tumor cell density maps), or other measures or predictions of biological features (e.g., tumor cell density). The hybrid models have capabilities of learning individual-specific relationships between imaging features and biological features.
    Type: Application
    Filed: November 19, 2018
    Publication date: October 29, 2020
    Inventors: Leland S. Hu, Jing Li, Kristin R. Swanson, Teresa Wu, Nathan Gaw, Hyunsoo Yoon, Andrea Hawkins-Daarud