Patents by Inventor Ishan Taneja

Ishan Taneja 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: 20230368070
    Abstract: A system for adapting a machine learning model for a specific population. The system includes a processor and memory devices storing instructions that configure the memory devices to perform operations. The operations may include receive a local dataset comprising local records of patients associated with the healthcare facility, perform a clustering function, and retrieving a template dataset comprising template records organized in clusters with variable centroids. The operations may also include calculating a similarity metric between the local and template records, generating a synthetic dataset by combining template and local records, segregating the synthetic dataset into a training synthetic dataset and a testing synthetic dataset, and generating and/or validating a machine learning predictive model by tuning a template model according to the training synthetic dataset and/or generating a new predictive model.
    Type: Application
    Filed: October 1, 2021
    Publication date: November 16, 2023
    Inventors: Akhil BHARGAVA, Ishan TANEJA, Carlos G. LOPEZ-ESPINA, Bobby REDDY, Sihai Dave ZHAO, Ruoqing ZHU
  • Publication number: 20230040185
    Abstract: A method for making dynamic risk predictions is provided. The method includes receiving a dataset with a first data field and a second data field. The first data field is populated with a measured value. The method also includes imputing a first predicted value to the second data field, generating a first risk score and a first set of associated metrics based on the measured value and the first predicted value, and imputing a second predicted value to the second data field. The method also includes calculating a statistically derived metric and determining whether the statistically derived metric exceeds a predetermined threshold, wherein a predetermined action is recommended if the statistically derived metric exceeds the predetermined threshold. A system and a non-transitory, computer readable medium storing instructions to cause the system to perform the above method are also provided.
    Type: Application
    Filed: January 12, 2021
    Publication date: February 9, 2023
    Inventors: Ishan Taneja, Carlos G. Lopez-Espina, Sihai Dave Zhao, Ruoqing Zhu, Bobby Reddy, Jr.
  • Publication number: 20230042330
    Abstract: A method for ranking an unmeasured feature for an instance given at least one feature is measured is provided. The method includes imputing a first value to the unmeasured feature in the instance while holding the other remaining unmeasured features constant and evaluating a first outcome with a model using the first value in the instance. The method includes imputing a second value to the unmeasured feature in the dataset while holding the other remaining unmeasured features constant, evaluating a second outcome with the model using the second value in the instance, and determining a statistical parameter with the first outcome and the second outcome. The method also includes assigning the unmeasured feature a ranking corresponding to the determined statistical parameter. A system and a non-transitory, computer readable medium storing instructions to perform the above method are also presented.
    Type: Application
    Filed: January 12, 2021
    Publication date: February 9, 2023
    Inventors: Ishan Taneja, Carlos G. Lopez-Espina, Sihai Dave Zhao, Ruoqing Zhu, Bobby Reddy, JR.