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    TELEHEALTH PLATFORM WITH ENHANCED MULTI-LEVEL CONSULTATION MATCHING AND COMMAND CENTER
    1.
    发明公开
    TELEHEALTH PLATFORM WITH ENHANCED MULTI-LEVEL CONSULTATION MATCHING AND COMMAND CENTER 审中-公开

    公开(公告)号：US20230282370A1

    公开(公告)日：2023-09-07

    申请号：US17994160

    申请日：2022-11-25

    Applicant: TELADOC HEALTH, INC.

    Inventor： Keith Weinberg ,  Peter H. Burkhardt ,  Ari Rasekh

    IPC: G16H80/00 ,  G16H40/20

    CPC classification number: G16H80/00 ,  G16H40/20

    Abstract: To address the complexity associated with matching telehealth consult requests with appropriate providers, a telehealth platform in accordance with the disclosure employs a multi-level matching system that first divides a set of consultation requests into one or more subsets or “virtual waiting rooms” having certain consultation criteria in common. The matching system then orders or prioritizes the requests within each virtual waiting room according to certain other criteria, such as urgency. Providers are assigned to one or more waiting rooms based on whether their provider profiles satisfy the consultation criteria of each waiting room. In addition, the set of providers assigned to a virtual waiting room may be ordered or prioritized according to further criteria. The highest priority provider assigned to a virtual waiting room may then be matched with the highest priority consultation request within that waiting room.

    ACCURACY IN BLOOD GLOCUSE MEASUREMENT USING PREDICTIVE THERMAL MODELING
    2.
    发明申请
    ACCURACY IN BLOOD GLOCUSE MEASUREMENT USING PREDICTIVE THERMAL MODELING 有权

    公开(公告)号：US20230089803A1

    公开(公告)日：2023-03-23

    申请号：US17734970

    申请日：2022-05-02

    Applicant: TELADOC HEALTH, INC.

    Inventor： Douglas Yuk ,  Randy Buswell ,  Gene V. Kozin ,  Yongbo Wang ,  Frederick Barrigar

    IPC: B01L3/00 ,  G01K1/02 ,  G01K7/22 ,  C12Q1/26

    Abstract: System, method, and computer program product for improving the accuracy of blood glucose measurements in a blood glucose meter by compensating for thermal effects of the glucose meter hardware. A machine learning model is used to predict the reaction site temperature on a blood glucose test strip based on one or more temperature measurements and device status information. The model receives several inputs including at least one temperature measurement sensed near the reaction site as well as device usage and other factors that may influence the reaction site temperature. The model provides a predicted reaction site temperature to the glucometer software or firmware to be used in a blood glucose calculation.
    1.

    FASTENING SYSTEM USING AN AXIALLY MAGNETIZED THREADED INSERT
    6.
    发明公开
    FASTENING SYSTEM USING AN AXIALLY MAGNETIZED THREADED INSERT 审中-公开

    公开(公告)号：US20240309904A1

    公开(公告)日：2024-09-19

    申请号：US18671223

    申请日：2024-05-22

    Applicant: TELADOC HEALTH, INC.

    Inventor： Daniel Steven Sanchez ,  Franco Medus

    IPC: F16B33/02

    CPC classification number: F16B33/02

    Abstract: Disclosed is an improved fastening system that leverages magnetism to assist in the installation of a fastener. The system may include an axially magnetized insert adapted to be secured within a bore in a surrounding material. The insert may be composed of a material having a magnetic permeability that is higher than that of the surrounding material. The insert may include a helical threaded interior surface adapted to receive a ferromagnetic screw. When placed in proximity of the insert, the tip of the screw is pulled into and held in alignment with the insert by the magnetic field emanating from the magnet. The fastening system may be particularly beneficial in environments where positioning or holding the screw in the starting position is difficult.

    FASTENING SYSTEM USING AN AXIALLY MAGNETIZED THREADED INSERT
    8.
    发明公开
    FASTENING SYSTEM USING AN AXIALLY MAGNETIZED THREADED INSERT 审中-公开

    公开(公告)号：US20230184283A1

    公开(公告)日：2023-06-15

    申请号：US18064063

    申请日：2022-12-09

    Applicant: TELADOC HEALTH, INC.

    Inventor： Daniel Steven Sanchez ,  Franco Medus

    IPC: F16B33/02

    CPC classification number: F16B33/02

    Abstract: Disclosed is an improved fastening system that leverages magnetism to assist in the installation of a fastener. The system may include an axially magnetized insert adapted to be secured within a bore in a surrounding material. The insert may be composed of a material having a magnetic permeability that is higher than that of the surrounding material. The insert may include a helical threaded interior surface adapted to receive a ferromagnetic screw. When placed in proximity of the insert, the tip of the screw is pulled into and held in alignment with the insert by the magnetic field emanating from the magnet. The fastening system may be particularly beneficial in environments where positioning or holding the screw in the starting position is difficult.

    MENTAL HEALTH RISK DETECTION USING GLUCOMETER DATA
    10.
    发明申请
    MENTAL HEALTH RISK DETECTION USING GLUCOMETER DATA 有权

    公开(公告)号：US20220406465A1

    公开(公告)日：2022-12-22

    申请号：US17590384

    申请日：2022-02-01

    Applicant: TELADOC HEALTH, INC.

    Inventor： Jessica Yu ,  Carter Chiu ,  Yajuan Wang ,  Eldin Dzubur ,  Wei Lu ,  Julia Hoffman

    IPC: G16H50/30

    Abstract: A system, method, and computer program product for passively informed mental health risk prediction. The system may include receiving mental health risk input signals from a blood glucometer and other devices. The mental health risk signals may include glucometer data, demographic data, and other data. The glucometer data for the subject may include at least one blood glucose value. The mental health risk input signals are input into a machine learning system. The machine learning system has been previously trained with mental health risk input signals and mental health status data for a plurality of subjects. The machine learning system outputs a prediction of mental health risk for the subject. The machine learning system may comprise a neural network.

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