Patents by Inventor Lucy Dao-Ke He

Lucy Dao-Ke He 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: 11848081
    Abstract: Systems and methods are disclosed for monitoring models for bias. In one implementation, a system for automatically assessing a deployed model for selection of a cohort may include a processing device programmed to: apply the deployed model to data representing a first plurality of individuals, the data including at least one characteristic of the first plurality of individuals; based on the application, select a subset of the first plurality of individuals as a cohort; receive data representing a second plurality of individuals labeled as within the cohort, the data including the at least one characteristic of the second plurality of individuals; compare the selected subset and the second plurality of individuals along the at least one characteristic; and determine whether the comparison results in a difference between the selected subset and the second plurality of individuals greater than a threshold.
    Type: Grant
    Filed: May 6, 2019
    Date of Patent: December 19, 2023
    Assignee: Flatiron Health, Inc.
    Inventors: Benjamin Edward Birnbaum, Joshua Daniel Haimson, Lucy Dao-Ke He, Melissa Hedberg, Nathan Coleman Nussbaum, Paul Stephen Richardson, Katharina Nicola Seidl-Rathkopf, Evan Eino Estola, Peter Daniel Larson
  • Patent number: 11734601
    Abstract: Systems and methods are disclosed for selecting cohorts. In one implementation, a model-assisted selection system for identifying candidates for placement into a cohort includes a data interface and at least one processing device. The at least one processing device is programmed to access, via the data interface, a database from which feature vectors associated with an individual from among a population of individuals can be derived; derive, for the individual, one or more feature vectors from the database; provide the one or more feature vectors to a model; receive an output from the model; and determine whether the individual from among the population of individuals is a candidate for the cohort based on the output received from the model.
    Type: Grant
    Filed: May 3, 2019
    Date of Patent: August 22, 2023
    Assignee: Flatiron Health, Inc.
    Inventors: Benjamin Edward Birnbaum, Joshua Daniel Haimson, Lucy Dao-Ke He, Katharina Nicola Seidl-Rathkopf, Monica Nayan Agrawal, Nathan Nussbaum
  • Patent number: 11694777
    Abstract: Systems and methods are disclosed for monitoring models for bias. In one implementation, a system for automatically assessing a deployed model for selection of a cohort may include a processing device programmed to: apply the deployed model to data representing a first plurality of individuals, the data including at least one characteristic of the first plurality of individuals; based on the application, select a subset of the first plurality of individuals as a cohort; receive data representing a second plurality of individuals labeled as within the cohort, the data including the at least one characteristic of the second plurality of individuals; compare the selected subset and the second plurality of individuals along the at least one characteristic; and determine whether the comparison results in a difference between the selected subset and the second plurality of individuals greater than a threshold.
    Type: Grant
    Filed: October 5, 2018
    Date of Patent: July 4, 2023
    Assignee: Flatiron Health, Inc.
    Inventors: Benjamin Edward Birnbaum, Joshua Daniel Haimson, Lucy Dao-Ke He, Melissa Hedberg, Nathan Coleman Nussbaum, Paul Stephen Richardson, Katharina Nicola Seidl-Rathkopf, Evan Eino Estola, Peter Daniel Larson
  • Publication number: 20200058382
    Abstract: Systems and methods are disclosed for monitoring models for bias. In one implementation, a system for automatically assessing a deployed model for selection of a cohort may include a processing device programmed to: apply the deployed model to data representing a first plurality of individuals, the data including at least one characteristic of the first plurality of individuals; based on the application, select a subset of the first plurality of individuals as a cohort; receive data representing a second plurality of individuals labeled as within the cohort, the data including the at least one characteristic of the second plurality of individuals; compare the selected subset and the second plurality of individuals along the at least one characteristic; and determine whether the comparison results in a difference between the selected subset and the second plurality of individuals greater than a threshold.
    Type: Application
    Filed: October 5, 2018
    Publication date: February 20, 2020
    Applicant: Flatiron Health, Inc.
    Inventors: Benjamin Edward Birnbaum, Joshua Daniel Haimson, Lucy Dao-Ke He, Melissa Hedberg, Nathan Coleman Nussbaum, Paul Stephen Richardson, Katharina Nicola Seidl-Rathkopf, Evan Eino Estola, Peter Daniel Larson
  • Publication number: 20200058383
    Abstract: Systems and methods are disclosed for monitoring models for bias. In one implementation, a system for automatically assessing a deployed model for selection of a cohort may include a processing device programmed to: apply the deployed model to data representing a first plurality of individuals, the data including at least one characteristic of the first plurality of individuals; based on the application, select a subset of the first plurality of individuals as a cohort; receive data representing a second plurality of individuals labeled as within the cohort, the data including the at least one characteristic of the second plurality of individuals; compare the selected subset and the second plurality of individuals along the at least one characteristic; and determine whether the comparison results in a difference between the selected subset and the second plurality of individuals greater than a threshold.
    Type: Application
    Filed: May 6, 2019
    Publication date: February 20, 2020
    Applicant: Flatiron Health, Inc.
    Inventors: Benjamin Edward Birnbaum, Joshua Daniel Haimson, Lucy Dao-Ke He, Melissa Hedberg, Nathan Coleman Nussbaum, Paul Stephen Richardson, Katharina Nicola Seidl-Rathkopf, Evan Eino Estola, Peter Daniel Larson
  • Publication number: 20190258950
    Abstract: Systems and methods are disclosed for selecting cohorts. In one implementation, a model-assisted selection system for identifying candidates for placement into a cohort includes a data interface and at least one processing device. The at least one processing device is programmed to access, via the data interface, a database from which feature vectors associated with an individual from among a population of individuals can be derived; derive, for the individual, one or more feature vectors from the database; provide the one or more feature vectors to a model; receive an output from the model; and determine whether the individual from among the population of individuals is a candidate for the cohort based on the output received from the model.
    Type: Application
    Filed: May 3, 2019
    Publication date: August 22, 2019
    Inventors: Benjamin Edward Birnbaum, Joshua Daniel Haimson, Lucy Dao-Ke He, Katharina Nicola Seidl-Rathkopf, Monica Nayan Agrawal, Nathan Nussbaum
  • Patent number: 10304000
    Abstract: Systems and methods are disclosed for selecting cohorts. In one implementation, a model-assisted selection system for identifying candidates for placement into a cohort includes a data interface and at least one processing device. The at least one processing device is programmed to access, via the data interface, a database from which feature vectors associated with an individual from among a population of individuals can be derived; derive, for the individual, one or more feature vectors from the database; provide the one or more feature vectors to a model; receive an output from the model; and determine whether the individual from among the population of individuals is a candidate for the cohort based on the output received from the model.
    Type: Grant
    Filed: April 12, 2018
    Date of Patent: May 28, 2019
    Assignee: Flatiron Health, Inc.
    Inventors: Benjamin Edward Birnbaum, Joshua Daniel Haimson, Lucy Dao-Ke He, Katharina Nicola Seidl-Rathkopf, Monica Nayan Agrawal, Nathan Nussbaum
  • Publication number: 20180300640
    Abstract: Systems and methods are disclosed for selecting cohorts. In one implementation, a model-assisted selection system for identifying candidates for placement into a cohort includes a data interface and at least one processing device. The at least one processing device is programmed to access, via the data interface, a database from which feature vectors associated with an individual from among a population of individuals can be derived; derive, for the individual, one or more feature vectors from the database; provide the one or more feature vectors to a model; receive an output from the model; and determine whether the individual from among the population of individuals is a candidate for the cohort based on the output received from the model.
    Type: Application
    Filed: April 12, 2018
    Publication date: October 18, 2018
    Inventors: Benjamin Edward Birnbaum, Joshua Daniel Haimson, Lucy Dao-Ke He, Katharina Nicola Seidl-Rathkopf, Monica Nayan Agrawal, Nathan Nussbaum