Patents by Inventor Ed Rubenstein

Ed Rubenstein 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: 20190371468
    Abstract: Systems and methods are provided for predicting treatment-regimen-related outcomes (e.g., risks of regimen-related toxicities). A predictive model is determined for predicting treatment-regimen-related outcomes and applied to a plurality of datasets. An ensemble algorithm is applied on result data generated from the application of the predictive model. Treatment-regimen-related outcomes are predicted using the predictive model. A combination of machine learning prediction and patient preference assessment is provided for enabling informed consent and precise treatment decisions.
    Type: Application
    Filed: August 19, 2019
    Publication date: December 5, 2019
    Inventors: Ed Rubenstein, Stephen T. Sonis, Carl De Moor
  • Patent number: 10475539
    Abstract: Systems and methods are provided for predicting treatment-regimen-related outcomes (e.g., risks of regimen-related toxicities). A predictive model is determined for predicting treatment-regimen-related outcomes and applied to a plurality of datasets. An ensemble algorithm is applied on result data generated from the application of the predictive model. Treatment-regimen-related outcomes are predicted using the predictive model. A combination of machine learning prediction and patient preference assessment is provided for enabling informed consent and precise treatment decisions.
    Type: Grant
    Filed: April 16, 2018
    Date of Patent: November 12, 2019
    Assignee: Inform Genomics, Inc.
    Inventors: Ed Rubenstein, Stephen T. Sonis, Carl De Moor
  • Publication number: 20180233230
    Abstract: Systems and methods are provided for predicting treatment-regimen-related outcomes (e.g., risks of regimen-related toxicities). A predictive model is determined for predicting treatment-regimen-related outcomes and applied to a plurality of datasets. An ensemble algorithm is applied on result data generated from the application of the predictive model. Treatment-regimen-related outcomes are predicted using the predictive model. A combination of machine learning prediction and patient preference assessment is provided for enabling informed consent and precise treatment decisions.
    Type: Application
    Filed: April 16, 2018
    Publication date: August 16, 2018
    Inventors: Ed Rubenstein, Stephen T. Sonis, Carl De Moor
  • Publication number: 20180226153
    Abstract: Systems and methods are provided for predicting treatment-regimen-related outcomes (e.g., risks of regimen-related toxicities). A predictive model is determined for predicting treatment-regimen-related outcomes and applied to a plurality of datasets. An ensemble algorithm is applied on result data generated from the application of the predictive model. Treatment-regimen-related outcomes are predicted using the predictive model. A combination of machine learning prediction and patient preference assessment is provided for enabling informed consent and precise treatment decisions.
    Type: Application
    Filed: March 29, 2018
    Publication date: August 9, 2018
    Inventors: Ed Rubenstein, Stephen T. Sonis, Carl De Moor