Patents by Inventor Harsha Arcot

Harsha Arcot 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: 12293835
    Abstract: An improved machine learning based method for authorizing the performance of a treatment, comprising the steps of: receiving a treatment authorization request, the treatment authorization request including a historical record of the person who will receive the treatment and treatment identifying information relating to the treatment; creating an extracted text of the historical record using optical character recognition on the historical record; determining whether to analyze authorization performance of the treatment using a machine learning authorization process, wherein the determination is based on treatment identifying information and whether treatment authorization guidelines exist for the identified treatment; in response to a determination to analyze authorization performance of the treatment using a machine learning authorization process: identifying authorization criteria for the treatment based on the treatment authorization guidelines, wherein the authorization criteria includes records data condi
    Type: Grant
    Filed: April 13, 2023
    Date of Patent: May 6, 2025
    Assignee: Elevance Health, Inc.
    Inventors: Ayush Mathur, Brian Fornelli, Xiaoyu Sun, Xinkai Chen, James D. Martindale, Harsha Arcot, Madeline Glasheen, Summer Ashley, Stephanie Wilson-English, Anthony Nguyen, Vincent Pantone, Urmesh Shah, Chao Zhang, Pice Chen, Adarsh Ramesh
  • Publication number: 20240290499
    Abstract: A system and method of predicting a medical diagnosis is disclosed. The method includes receiving claims data, clinical data and demographic data and detecting a prediction target for the diagnosis. If present, inputting the prediction indicator and the clinical data into a machine learning model to predict diagnosis risk, to create a diagnosis risk score; determining a care seeking propensity score, from the demographic data; weighting the diagnosis risk score by the care seeking propensity score to create a weighted diagnosis risk score; determining whether the weighted diagnosis risk score indicates a likelihood of the medical diagnosis; and, in response, transmitting a recommendation for further evaluation. The machine learning model may be trained using historical claims data, clinical data, and demographic data and may be trained to detect correlation between medical diagnosis signals identified from the training data, and a positive result from a screening mechanism the medical diagnosis.
    Type: Application
    Filed: February 26, 2024
    Publication date: August 29, 2024
    Inventors: Eugene Hsu, Jessica Feeney, Joon-Ku Im, Keea Taylor, Haoyun Feng, Anthony Nguyen, Ayush Mathur, Harsha Arcot, Shawn Wang