Patents by Inventor George Sirbu

George Sirbu 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: 20250022613
    Abstract: A computer-implemented method for differentiating patterns of care (DPoC) to detect anomalous subsets in any given population with a defined set of outcomes and features. The computer-implemented method includes detecting the anomalous subsets, ranking the anomalous subsets based on a score of each anomalous subset that is reflective of an anomaly thereof, specifying whether each of the anomalous subsets overlaps with another one of the anomalous subsets, whether each of the anomalous subsets is unique and whether each of the anomalous subsets is conditional and specifying as to whether the detecting of each of the anomalous subsets has a higher or lower outcome than expected.
    Type: Application
    Filed: July 14, 2023
    Publication date: January 16, 2025
    Inventors: George Sirbu, William Ogallo, Girmaw Abebe Tadesse, Feng Xin, Ajay Ashok Deshpande, Charles Muchiri Wachira, Aisha Walcott, Vibha Anand, Brandi Hodor, Zainab Savliwala, Isaiah Mulang' Onando
  • Publication number: 20240135034
    Abstract: One or more computer processors discover an anomalous subset through sparsity-based automatic feature selection.
    Type: Application
    Filed: October 11, 2022
    Publication date: April 25, 2024
    Inventors: Girmaw Abebe Tadesse, William Ogallo, George Sirbu, Aisha Walcott, Skyler Speakman
  • Patent number: 11948694
    Abstract: Mechanisms are provided for compartmental epidemiological computer modeling based on mobility data. Machine learning training of an isolation rate prediction computer model is performed to generate a trained isolation rate prediction model that predicts an isolation rate of a biological population. Isolation data is received which comprises data indicating a measure of mobility of the biological population. The trained isolation rate prediction model is executed on input features extracted from the isolation data to generate a predicted isolation rate. A compartmental epidemiological computer model, comprising a plurality of compartments representing states of a population with regard to an infectious disease, is executed to simulate a progression of the infectious disease and flows of portions of the population from between compartments in the compartmental epidemiological computer model are controlled based on the predicted isolation rate.
    Type: Grant
    Filed: May 12, 2021
    Date of Patent: April 2, 2024
    Inventors: Vishrawas Gopalakrishnan, Sayali Navalekar, James H. Kaufman, Simone Bianco, Kun Hu, Ajay Ashok Deshpande, Sarah Kefayati, Ujwal Reddy Moramganti, George Sirbu, Xuan Liu, Raman Srinivasan, Pan Ding
  • Publication number: 20220367067
    Abstract: Mechanisms are provided for compartmental epidemiological computer modeling based on mobility data. Machine learning training of an isolation rate prediction computer model is performed to generate a trained isolation rate prediction model that predicts an isolation rate of a biological population. Isolation data is received which comprises data indicating a measure of mobility of the biological population. The trained isolation rate prediction model is executed on input features extracted from the isolation data to generate a predicted isolation rate. A compartmental epidemiological computer model, comprising a plurality of compartments representing states of a population with regard to an infectious disease, is executed to simulate a progression of the infectious disease and flows of portions of the population from between compartments in the compartmental epidemiological computer model are controlled based on the predicted isolation rate.
    Type: Application
    Filed: May 12, 2021
    Publication date: November 17, 2022
    Inventors: Vishrawas Gopalakrishnan, Sayali Navalekar, James H. Kaufman, Simone Bianco, Kun Hu, Ajay Ashok Deshpande, Sarah Kefayati, Ujwal Reddy Moramganti, George Sirbu, Xuan Liu, Raman Srinivasan, Pan Ding
  • Publication number: 20220336108
    Abstract: A mechanism is provided in a data processing system to implement a model pipeline for predicting changes in disease transmission rate using a spatial temporal epidemiological model. The mechanism receives input data comprising disease case data for a disease and mobility data and prepares the input data to generate a training dataset, a validation dataset, and a test dataset. A feature selection module performs feature selection on the input data to select a first set of features for a binary classification computer model, a second set of features for a three-level classification computer model, and a third set of features for a regression computer model.
    Type: Application
    Filed: April 14, 2021
    Publication date: October 20, 2022
    Inventors: George Sirbu, Ujwal Reddy Moramganti, Sayali Navalekar, Vishrawas Gopalakrishnan, Ajay Ashok Deshpande, Sarah Kefayati, Pan Ding, Raman Srinivasan, Xuan Liu, James H. Kaufman
  • Patent number: 10535430
    Abstract: A method and system for grouping medical claims data, including outpatient medical claims, into medical events for further analysis is disclosed. Historical outpatient medical claims data is first aggregated by one or more categorization schemes, and then grouped by patient and date. Once the outpatient medical claims data is aggregated and grouped, the methods disclosed build outpatient events by further grouping together disparate medical claims data records that represent a single encounter with an outpatient healthcare system. The outpatient events may be used for analyzing aspects of outpatient care.
    Type: Grant
    Filed: July 25, 2014
    Date of Patent: January 14, 2020
    Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
    Inventors: Anne Elizabeth Fischer, Dennis Dunn, Gary Pickens, Elisse Jane Moldwin, Peter Mark Bouman, George Sirbu
  • Publication number: 20190237199
    Abstract: A method of population classification to identify the likely level of care management interventions appropriate for individuals, for use in a population health management system, the method including: receiving, by a processing engine, medical claims data for an individual; reviewing, by the processing engine, a plurality of predetermined parameters within the medical claims data for the individual; classifying, by the processing engine, the individual into one of a plurality of predetermined intervention groups, based on reviewing the plurality of predetermined parameters; and providing to the population health management system, by the processing engine, a level of care management appropriate for the individual based on the predetermined intervention group in which the individual was classified.
    Type: Application
    Filed: January 30, 2018
    Publication date: August 1, 2019
    Inventors: Anne E. Fischer, Robert P. Kelley, Amy G. Brown, Janet K. Young, George Sirbu, Christopher A. Gagen, Matthew R. Alter, Therese R. Gorski