Patents by Inventor Julius Fridriksson

Julius Fridriksson 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).

  • Machine learning to identify locations of brain injury
    Patent number: 11557400
    Abstract: The present disclosure provides systems and methods that include or otherwise leverage a machine-learned brain injury location model to predict locations of brain injury in a patient based on test data associated with the patient, such as, for example, behavioral test data. For example, the machine-learned brain injury location model can be trained on training data associated with a corpus of patients, where the training data includes sets of example test data (e.g., behavioral test data) respectively labeled with ground truth brain injury locations.
    Type: Grant
    Filed: January 5, 2021
    Date of Patent: January 17, 2023
    Assignee: University of South Carolina
    Inventors: Julius Fridriksson, Christopher Rorden
  • Machine Learning to Identify Locations of Brain Injury
    Publication number: 20210125727
    Abstract: The present disclosure provides systems and methods that include or otherwise leverage a machine-learned brain injury location model to predict locations of brain injury in a patient based on test data associated with the patient, such as, for example, behavioral test data. For example, the machine-learned brain injury location model can be trained on training data associated with a corpus of patients, where the training data includes sets of example test data (e.g., behavioral test data) respectively labeled with ground truth brain injury locations.
    Type: Application
    Filed: January 5, 2021
    Publication date: April 29, 2021
    Inventors: JULIUS FRIDRIKSSON, CHRISTOPHER RORDEN
  • Machine learning to identify locations of brain injury
    Patent number: 10916348
    Abstract: The present disclosure provides systems and methods that include or otherwise leverage a machine-learned brain injury location model to predict locations of brain injury in a patient based on test data associated with the patient, such as, for example, behavioral test data. For example, the machine-learned brain injury location model can be trained on training data associated with a corpus of patients, where the training data includes sets of example test data (e.g., behavioral test data) respectively labeled with ground truth brain injury locations.
    Type: Grant
    Filed: December 12, 2018
    Date of Patent: February 9, 2021
    Assignee: University of South Carolina
    Inventors: Julius Fridriksson, Christopher Rorden
  • Machine Learning to Identify Locations of Brain Injury
    Publication number: 20190180878
    Abstract: The present disclosure provides systems and methods that include or otherwise leverage a machine-learned brain injury location model to predict locations of brain injury in a patient based on test data associated with the patient, such as, for example, behavioral test data. For example, the machine-learned brain injury location model can be trained on training data associated with a corpus of patients, where the training data includes sets of example test data (e.g., behavioral test data) respectively labeled with ground truth brain injury locations.
    Type: Application
    Filed: December 12, 2018
    Publication date: June 13, 2019
    Inventors: Julius Fridriksson, Christopher Rorden