Patents by Inventor Gregory Rule

Gregory Rule 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).

  • Circulatory shock prediction and diagnosis model
    Patent number: 12763219
    Abstract: Systems, methods, and computer-readable media for determining the probability of a patient developing shock. The method includes receiving, at a client device, a first set of vital sign measurements from the patient associated with a first time. The method includes determining, using a time-variant machine learning model, the probability of the patient developing shock based on the first set of vital sign measurements, the time-variant machine learning model having a first set of parameters associated with the first time. The method includes receiving, at the client device, a second set of vital sign measurements from the patient associated with a second time. The method includes updating, using the time-variant machine learning model, the probability of the patient developing shock based on the second set of vital sign measurements, the time-variant machine learning model having a second set of parameters associated with the second time.
    Type: Grant
    Filed: October 2, 2024
    Date of Patent: October 13, 2026
    Assignee: Applied Research Associates, Inc.
    Inventors: Adam Amos-Binks, Christopher Nemeth, Gregory Rule
  • CIRCULATORY SHOCK PREDICTION AND DIAGNOSIS MODEL
    Publication number: 20260094719
    Abstract: Systems, methods, and computer-readable media for determining the probability of a patient developing shock. The method includes receiving, at a client device, a first set of vital sign measurements from the patient associated with a first time. The method includes determining, using a time-variant machine learning model, the probability of the patient developing shock based on the first set of vital sign measurements, the time-variant machine learning model having a first set of parameters associated with the first time. The method includes receiving, at the client device, a second set of vital sign measurements from the patient associated with a second time. The method includes updating, using the time-variant machine learning model, the probability of the patient developing shock based on the second set of vital sign measurements, the time-variant machine learning model having a second set of parameters associated with the second time.
    Type: Application
    Filed: October 2, 2024
    Publication date: April 2, 2026
    Inventors: Adam Amos-Binks, Christopher Nemeth, Gregory Rule