Patents by Inventor Naiqian Zhi

Naiqian Zhi 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: 20230307127
    Abstract: A system and method are disclosed for predicting short term health outcomes based on data collected by a wearable device such as an activity tracker or a smart watch. Artificial Intelligence (AI) algorithms are configured to process an input vector that includes monitored parameter data collected by the wearable device as well as embedding data obtained from health records corresponding to a user account registered to the wearable device. In particular, a framework is defined that includes a random forest model configured to classify a user based on the monitored parameter data and embedding data. Based on a positive health outcome classification, a minimum value is assigned to a health index value for the user or, based on a negative health outcome classification, a gradient boosting machine is configured to generate the health index value. Various operations can be performed based on the assigned health index value for the user.
    Type: Application
    Filed: March 24, 2022
    Publication date: September 28, 2023
    Inventors: Naiqian Zhi, Sarah Wohlman, Alex Xu, Ryan Berns, Rajiv Bhan
  • Publication number: 20230290502
    Abstract: A system and method are disclosed for detecting chronic health conditions based on data collected by a wearable device such as an activity tracker or a smart watch. Deep learning algorithms are configured to process the monitored parameter data collected by the wearable device as well as additional embedding data obtained from health records corresponding to a user account registered to the wearable device. In some examples, the input vector can also include embedding data related to social determinants data and/or demographic data. The output of the deep learning algorithms provides predictions that represent probabilities that the user of the wearable device has an underlying health condition. If any underlying health condition is detected, then the user can be notified directly, via the wearable device or an associated application or technology, or indirectly, via a primary care provider associated with the user.
    Type: Application
    Filed: March 10, 2022
    Publication date: September 14, 2023
    Inventors: Naiqian Zhi, Sarah Wohlman, Alex Xu, Ryan Berns, Rajiv Bhan, Sumeet Kumar, Alan Leggitt, Qin Li
  • Publication number: 20210401295
    Abstract: A system and method are disclosed for monitoring health conditions based on data collected by a wearable device such as an activity tracker or a smart watch. Deep learning algorithms are configured to process an input vector that includes monitored parameter data collected by the wearable device as well as embedding data obtained from health records corresponding to a user account registered to the wearable device. In some embodiments, the input vector can also include social determinants data and/or demographic data. The output of the deep learning algorithms provides classifiers that represent probabilities that the user of the wearable device has an underlying health condition. If any underlying health condition is detected, then the user can be notified directly, via the wearable device or an associated application or technology, or indirectly, via a primary care provider associated with the user.
    Type: Application
    Filed: June 29, 2020
    Publication date: December 30, 2021
    Inventors: Naiqian Zhi, Benjamin Wanamaker, Rajiv Bhan, Sumeet Kumar
  • Publication number: 20210407667
    Abstract: A system and method are disclosed for predicting unnecessary emergency room visits based on data collected by a wearable device such as an activity tracker or a smart watch. Artificial Intelligence (AI) algorithms are configured to process an input vector that includes monitored parameter data collected by the wearable device as well as embedding data obtained from health records corresponding to a user account registered to the wearable device. The output of the AI algorithms provides classifiers that represent probabilities that the user of the wearable device is likely to experience one or more acute events within a specific time frame or time frames. The acute event can include an emergency room visit, which may be classified as unnecessary and/or preventable, and the user can be notified directly, via the wearable device or an associated application or technology, to attempt to deter preventable emergency room visits.
    Type: Application
    Filed: June 29, 2021
    Publication date: December 30, 2021
    Inventors: Naiqian Zhi, Benjamin Wanamaker, Rajiv Bhan, Sumeet Kumar