Patents by Inventor Travis R. Frosch

Travis R. Frosch 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).

  • Publication number: 20240185989
    Abstract: A computer-implemented system is provided that includes a plurality of endpoint databases employed to store medical images and metadata that describes attributes of the respective medical images. A management and orchestration platform periodically scans the endpoint databases to determine an index of the recently acquired medical images and associated metadata and updates to metadata associated with previously stored medical images. A search engine executes the search function to retrieve at least one of the recently acquired medical images and associated metadata and the recent updates to metadata associated with the previously stored medical images. The platform can also provide project management services and various collaborative, social networking type services. For example, the platform can facilitate collaborative review of medical image data, allowing users to rate and review the medical image data, annotate the medical image data, edit and augment the medical image data, and the like.
    Type: Application
    Filed: February 14, 2024
    Publication date: June 6, 2024
    Inventors: Travis R. Frosch, Sylvain Adam, Garry M. Whitley, Heather Mc Combs Chait, Steve M. Lawson
  • Patent number: 11935643
    Abstract: A computer-implemented system is provided that includes a plurality of endpoint databases employed to store medical images and metadata that describes attributes of the respective medical images. A management and orchestration platform periodically scans the endpoint databases to determine an index of the recently acquired medical images and associated metadata and updates to metadata associated with previously stored medical images. A search engine executes the search function to retrieve at least one of the recently acquired medical images and associated metadata and the recent updates to metadata associated with the previously stored medical images. The platform can also provide project management services and various collaborative, social networking type services. For example, the platform can facilitate collaborative review of medical image data, allowing users to rate and review the medical image data, annotate the medical image data, edit and augment the medical image data, and the like.
    Type: Grant
    Filed: November 24, 2020
    Date of Patent: March 19, 2024
    Assignee: GE PRECISION HEALTHCARE LLC
    Inventors: Travis R. Frosch, Sylvain Adam, Garry M. Whitley, Heather McCombs Chait, Steve M. Lawson
  • Publication number: 20220335328
    Abstract: Systems and techniques that facilitate automated machine learning model feedback with data capture and synthetic data generation are provided. In various embodiments, a receiver component can receive electronic input identifying a deployed machine learning model. In various aspects, a listener component can retrieve from a data pipeline a data candidate that has been analyzed by the deployed machine learning model, an inference generated by the deployed machine learning model based on the data candidate, and an expert conclusion provided by a subject matter expert based on the data candidate. In various instances, a comparison component can compare the inference with the expert conclusion to determine whether the inference is consistent with the expert conclusion. In various cases, an augmentation component can, in response to a determination that the inference is not consistent with the expert conclusion, generate a set of synthetic training data based on the data candidate.
    Type: Application
    Filed: April 20, 2021
    Publication date: October 20, 2022
    Inventors: Travis R. Frosch, Anastasia Marie Van Dyke Dunn, Garry M. Whitley, Alvaro Molina, Weston R. Olmstead
  • Patent number: 11475358
    Abstract: Techniques are provided for enhancing the efficiency and accuracy of annotating data samples for supervised machine learning algorithms using an advanced annotation pipeline. According to an embodiment, a method can comprise collecting, by a system comprising a processor, unannotated data samples for input to a machine learning model and storing the unannotated data samples in an annotation queue. The method further comprises determining, by the system, annotation priority levels for respective unannotated data samples of the unannotated data samples, selecting, by the system from amongst different annotation techniques, one or more of the different annotation techniques for annotating the respective unannotated data samples based the annotation priority levels associated with the respective unannotated data samples.
    Type: Grant
    Filed: July 31, 2019
    Date of Patent: October 18, 2022
    Assignee: GE PRECISION HEALTHCARE LLC
    Inventors: Marc T. Edgar, Travis R. Frosch, Gopal B. Avinash, Garry M. Whitley
  • Publication number: 20210158933
    Abstract: A computer-implemented system is provided that includes a plurality of endpoint databases employed to store medical images and metadata that describes attributes of the respective medical images. A management and orchestration platform periodically scans the endpoint databases to determine an index of the recently acquired medical images and associated metadata and updates to metadata associated with previously stored medical images. A search engine executes the search function to retrieve at least one of the recently acquired medical images and associated metadata and the recent updates to metadata associated with the previously stored medical images. The platform can also provide project management services and various collaborative, social networking type services. For example, the platform can facilitate collaborative review of medical image data, allowing users to rate and review the medical image data, annotate the medical image data, edit and augment the medical image data, and the like.
    Type: Application
    Filed: November 24, 2020
    Publication date: May 27, 2021
    Inventors: Travis R. Frosch, Sylvain Adam, Garry M. Whitley, Heather Mc Combs Chait, Steve M. Lawson
  • Publication number: 20210034920
    Abstract: Techniques are provided for enhancing the efficiency and accuracy of annotating data samples for supervised machine learning algorithms using an advanced annotation pipeline. According to an embodiment, a method can comprise collecting, by a system comprising a processor, unannotated data samples for input to a machine learning model and storing the unannotated data samples in an annotation queue. The method further comprises determining, by the system, annotation priority levels for respective unannotated data samples of the unannotated data samples, selecting, by the system from amongst different annotation techniques, one or more of the different annotation techniques for annotating the respective unannotated data samples based the annotation priority levels associated with the respective unannotated data samples.
    Type: Application
    Filed: July 31, 2019
    Publication date: February 4, 2021
    Inventors: Marc T. Edgar, Travis R. Frosch, Gopal B. Avinash, Garry M. Whitley
  • Publication number: 20210035015
    Abstract: Techniques are provided for enhancing the efficiency and accuracy of annotating data samples for supervised machine learning algorithms using an advanced annotation pipeline. According to an embodiment, a method can comprise collecting, by a system comprising a processor, unannotated data samples for input to a machine learning model and storing the unannotated data samples in an annotation queue. The method further comprises determining, by the system, annotation priority levels for respective unannotated data samples of the unannotated data samples, selecting, by the system from amongst different annotation techniques, one or more of the different annotation techniques for annotating the respective unannotated data samples based the annotation priority levels associated with the respective unannotated data samples.
    Type: Application
    Filed: July 31, 2019
    Publication date: February 4, 2021
    Inventors: Marc T. Edgar, Travis R. Frosch, Gopal B. Avinash, Garry M. Whitley