Patents by Inventor John Weston HUGHES

John Weston HUGHES 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: 11921766
    Abstract: Described herein are technologies related to constructing supplemental content items that summarize electronic landing pages. A sequence to sequence model that is configured to construct supplemental content items is trained based upon a corpus of electronic landing pages and supplemental content items that have been constructed by domain experts, wherein each landing page has a respective supplemental content item assigned thereto. The sequence to sequence model is additionally trained using self critical sequence training, where estimated click through rates of supplemental content items generated by the sequence to sequence model are employed to train the sequence to sequence model.
    Type: Grant
    Filed: September 2, 2022
    Date of Patent: March 5, 2024
    Assignee: MICRSOFT TECHNOLOGY LICENSING, LLC
    Inventors: Keng-hao Chang, Ruofei Zhang, John Weston Hughes
  • Publication number: 20230346288
    Abstract: Systems and methods for predicting a future cardiovascular event are provided. Electrocardiogram waveform data can be acquired and utilized in a trained computational model to predict a future cardiovascular event. Clinical interventions, clinical surveillance, and clinical treatments can be performed based on a future cardiovascular event prediction.
    Type: Application
    Filed: April 28, 2023
    Publication date: November 2, 2023
    Applicant: The Board of Trustees of the Leland Stanford Junior University
    Inventors: John Weston Hughes, James Zou, Euan A. Ashley, Marco V. Perez
  • Publication number: 20220414134
    Abstract: Described herein are technologies related to constructing supplemental content items that summarize electronic landing pages. A sequence to sequence model that is configured to construct supplemental content items is trained based upon a corpus of electronic landing pages and supplemental content items that have been constructed by domain experts, wherein each landing page has a respective supplemental content item assigned thereto. The sequence to sequence model is additionally trained using self critical sequence training, where estimated click through rates of supplemental content items generated by the sequence to sequence model are employed to train the sequence to sequence model.
    Type: Application
    Filed: September 2, 2022
    Publication date: December 29, 2022
    Inventors: Keng-hao CHANG, Ruofei ZHANG, John Weston HUGHES
  • Patent number: 11449536
    Abstract: Described herein are technologies related to constructing supplemental content items that summarize electronic landing pages. A sequence to sequence model that is configured to construct supplemental content items is trained based upon a corpus of electronic landing pages and supplemental content items that have been constructed by domain experts, wherein each landing page has a respective supplemental content item assigned thereto. The sequence to sequence model is additionally trained using self critical sequence training, where estimated click through rates of supplemental content items generated by the sequence to sequence model are employed to train the sequence to sequence model.
    Type: Grant
    Filed: May 16, 2019
    Date of Patent: September 20, 2022
    Assignee: MICROSOFT TECHNOLOGY LICENSING, LLC
    Inventors: Keng-hao Chang, Ruofei Zhang, John Weston Hughes
  • Publication number: 20200364252
    Abstract: Described herein are technologies related to constructing supplemental content items that summarize electronic landing pages. A sequence to sequence model that is configured to construct supplemental content items is trained based upon a corpus of electronic landing pages and supplemental content items that have been constructed by domain experts, wherein each landing page has a respective supplemental content item assigned thereto. The sequence to sequence model is additionally trained using self critical sequence training, where estimated click through rates of supplemental content items generated by the sequence to sequence model are employed to train the sequence to sequence model.
    Type: Application
    Filed: May 16, 2019
    Publication date: November 19, 2020
    Inventors: Keng-hao CHANG, Ruofei ZHANG, John Weston HUGHES