Patents by Inventor Saikumar Chintareddy

Saikumar Chintareddy 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).

  • Weighted adaptive filtering based loss function to predict the first occurrence of multiple events in a single shot
    Patent number: 11741381
    Abstract: There is a need for more effective and efficient prediction data analysis. This need can be addressed by, for example, solutions for performing first-occurrence multi-disease prediction. In one example, a method includes determining a per-event-type loss value for each event type of a group of event types; determining a cross-event-type loss value based at least in part on each per-event-type loss value; training a multi-event-type prediction model based at least in part on the cross-event type loss value; generating a first-occurrence prediction based at least in part on the multi-event-type prediction model, wherein the first occurrence-prediction comprises a first-occurrence prediction item for each event type of the group of event types; and performing one or more prediction-based actions based at least in part on the first-occurrence prediction.
    Type: Grant
    Filed: July 14, 2020
    Date of Patent: August 29, 2023
    Assignee: OPTUM TECHNOLOGY, INC.
    Inventors: V Kishore Ayyadevara, Sree Harsha Ankem, Raghav Bali, Rohan Khilnani, Vineet Shukla, Saikumar Chintareddy, Ranraj Rana Singh
  • WEIGHTED ADAPTIVE FILTERING BASED LOSS FUNCTION TO PREDICT THE FIRST OCCURRENCE OF MULTIPLE EVENTS IN A SINGLE SHOT
    Publication number: 20220019913
    Abstract: There is a need for more effective and efficient prediction data analysis. This need can be addressed by, for example, solutions for performing first-occurrence multi-disease prediction. In one example, a method includes determining a per-event-type loss value for each event type of a group of event types; determining a cross-event-type loss value based at least in part on each per-event-type loss value; training a multi-event-type prediction model based at least in part on the cross-event type loss value; generating a first-occurrence prediction based at least in part on the multi-event-type prediction model, wherein the first occurrence-prediction comprises a first-occurrence prediction item for each event type of the group of event types; and performing one or more prediction-based actions based at least in part on the first-occurrence prediction.
    Type: Application
    Filed: July 14, 2020
    Publication date: January 20, 2022
    Inventors: V Kishore Ayyadevara, Sree Harsha Ankem, Raghav Bali, Rohan Khilnani, Vineet Shukla, Saikumar Chintareddy, Ranraj Rana Singh