Patents by Inventor Divine E. Ediebah

Divine E. Ediebah 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: 20240186019
    Abstract: Systems, apparatuses and methods may provide technology that automatically converts, by a machine learning model, a Shapley plot into a hazard ratio plot. The technology may also identify a set of preoperative baseline characteristics associated with a procedure on a pooled patient population, determine, by a machine learning model, a set of health failure probabilities for a target patient based on the set of preoperative baseline characteristic and a set of preoperative target characteristics, wherein the set of preoperative target characteristics correspond to the target client, and pair, by the machine learning model, each probability in the set of health failure probabilities with a postoperative dual antiplatelet therapy (DAPT) duration for the target patient.
    Type: Application
    Filed: November 20, 2023
    Publication date: June 6, 2024
    Inventors: Divine E. Ediebah, Jana R. Buccola, Ciaran Byrne
  • Patent number: 11996201
    Abstract: Systems, apparatuses and methods may provide technology that identifies minority class data and majority class data in patient-level data, wherein the minority class data corresponds to patients with a health failure and the majority class data corresponds to patients without the health failure, oversamples the minority class data to obtain synthetic class data and automatically reduces, via a machine learning classifier, a set of risk factor variables based on the majority class data, the minority class data and the synthetic class data.
    Type: Grant
    Filed: March 4, 2021
    Date of Patent: May 28, 2024
    Assignee: ABBOTT LABORATORIES
    Inventors: Divine E. Ediebah, Hajime Kusano, Ciaran A. Byrne, Krishnankutty Sudhir, Nick West
  • Publication number: 20220285028
    Abstract: Systems, apparatuses and methods may provide technology that identifies minority class data and majority class data in patient-level data, wherein the minority class data corresponds to patients with a health failure and the majority class data corresponds to patients without the health failure, oversamples the minority class data to obtain synthetic class data and automatically reduces, via a machine learning classifier, a set of risk factor variables based on the majority class data, the minority class data and the synthetic class data.
    Type: Application
    Filed: March 4, 2021
    Publication date: September 8, 2022
    Inventors: Divine E. Ediebah, Hajime Kusano, Ciaran A. Byrne, Krishnankutty Sudhir, Nick West