Patents by Inventor John Michael Jordan

John Michael Jordan 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).

  • Patent number: 12254717
    Abstract: An interactive portrait system includes a camera configured to capture imagery of an environment and a controller. The controller is configured to analyze the imagery to identify a guest in the environment, instruct an output device to provide an initial output to attempt to interact with the guest, and analyze the imagery to identify a behavior of the guest during the initial output, after the initial output, or both. The controller is also configured to evaluate the behavior of the guest using one or more artificial intelligence algorithms to determine whether the guest responded to the initial output. The controller is further configured to, in response to determining that the guest responded to the initial output, instruct the output device to provide an additional output to continue to attempt to interact with the guest.
    Type: Grant
    Filed: June 21, 2023
    Date of Patent: March 18, 2025
    Assignee: Universal City Studios LLC
    Inventors: Robert Michael Jordan, Anthony Melo, Angelo Pagliuca, Brandon David Burnette, John Adams, Jacob David Allinson, Eric To Chan, Mark James Traynor
  • Publication number: 20240335171
    Abstract: A waveform processing system including a patient monitor, a display device, and a processor configured to control the display device to display a location in a stream of waveform data of a segment including a specified event such as aberration or variation in the waveform data, wherein the location of the segment is identified based on aggregating outputs of an AI model performing sliding window inferences on the stream of waveform data. Performing the sliding window inferences on the stream of waveform data may include dividing the waveform data into a plurality of overlapping chunks, each chunk comprising consecutive data values extracted from the stream of waveform data over a specified duration, and inputting each chunk into the AI model to generate arrays of output values indicating a presence or absence the segment, which may then be aggregated.
    Type: Application
    Filed: April 4, 2023
    Publication date: October 10, 2024
    Inventors: Rohit Pardasani, Siddharth Ajith, John Michael Jordan, Renee L Vitullo, Merrinda Janas
  • Patent number: 12094611
    Abstract: Techniques are described for performing fetal heart rate (FHR) analytics using machine learning techniques. According to an embodiment, computer-implemented method comprises training a machine learning model using a supervised machine learning process to identify patterns in training cardiotocograph data that correspond to defined physiological events associated with respective fetuses and mothers of the fetuses represented in the training cardiotocograph data. The method further comprises receiving new cardiotocograph data for a fetus and mother in real-time over a period of labor and applying the machine learning model to the new cardiotocograph data as it is received to identify the patterns in the new cardiotocograph data.
    Type: Grant
    Filed: November 2, 2021
    Date of Patent: September 17, 2024
    Assignee: GE Precision Healthcare LLC
    Inventors: Rohit Pardasani, Siddharth Ajith, John Michael Jordan, Renee L Vitullo
  • Publication number: 20240282451
    Abstract: One or more systems, devices, computer-implemented methods and/or computer program products of use provided herein relate to artificial intelligence (AI) to generate labor and delivery-based predictions. A system can comprise a processor that can execute computer-executable components stored in memory, wherein the computer-executable components can comprise a first AI model that can generate first data comprising one or more labor and delivery predictions applicable to one or more fetuses and a mother of the one or more fetuses, during labor, by analyzing second data comprising cardiotocography (CTG) analysis data of the one or more fetuses and the mother generated by a second AI model and third data comprising maternal health analysis data of the mother generated by a third AI model, wherein the first AI model can be a multistage AI model comprising respective models directed to predicting respective ones of the one or more labor and delivery predictions.
    Type: Application
    Filed: April 10, 2024
    Publication date: August 22, 2024
    Inventors: Rohit Pardasani, Siddharth Ajith, John Michael Jordan
  • Publication number: 20230136298
    Abstract: Techniques are described for performing fetal heart rate (FHR) analytics using machine learning techniques. According to an embodiment, computer-implemented method comprises training a machine learning model using a supervised machine learning process to identify patterns in training cardiotocograph data that correspond to defined physiological events associated with respective fetuses and mothers of the fetuses represented in the training cardiotocograph data. The method further comprises receiving new cardiotocograph data for a fetus and mother in real-time over a period of labor and applying the machine learning model to the new cardiotocograph data as it is received to identify the patterns in the new cardiotocograph data.
    Type: Application
    Filed: November 2, 2021
    Publication date: May 4, 2023
    Inventors: Rohit Pardasani, Siddharth Ajith, John Michael Jordan, Renee L Vitullo