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    SYNTHETIC DIGITAL TWIN FOR A PATIENT
    1.
    发明申请
    SYNTHETIC DIGITAL TWIN FOR A PATIENT 有权

    公开(公告)号：US20250006367A1

    公开(公告)日：2025-01-02

    申请号：US18345537

    申请日：2023-06-30

    Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATION

    Inventor： Chen Wang ,  Bo Wen ,  Erhan Bilal

    IPC: G16H50/20 ,  G16H10/60 ,  G16H50/70

    Abstract: A method, computer program product, and computer system for generating synthetic time-series data for a specific disease. One or more processors of a computer system provide a generative adversarial network (GAN), train the GAN to generate time series data using episodic measurement results as metadata for a patient cohort with a specific disease; receive input metadata associated with an episodic measurement for a patient in the patient cohort with the specific disease by the trained GAN, and generate synthetic time series data that simulates the patient in the patient cohort with the specific disease.

    Electroencephalograph Signal Generation Speech in a Generative Adversarial Network
    2.
    发明申请
    Electroencephalograph Signal Generation Speech in a Generative Adversarial Network 有权

    公开(公告)号：US20250006174A1

    公开(公告)日：2025-01-02

    申请号：US18341867

    申请日：2023-06-27

    Applicant: International Business Machines Corporation

    Inventor： Erhan Bilal ,  Chen Wang ,  Bo Wen

    IPC: G10L13/04

    Abstract: A computer implemented method synthesizes electroencephalograph signals. A number of processor units creates a training dataset comprising real electroencephalograph signals, speech signals correlating to the real electroencephalograph signals, and a set of human characteristics for the real electroencephalograph signals. The number of processor units trains a generative adversarial network using the training dataset to create a trained generative adversarial network. The trained generative adversarial network generates synthetic electroencephalograph signals in response to receiving new speech signals.

    AUTOMATED LABELING OF USER SENSOR DATA
    4.
    发明公开
    AUTOMATED LABELING OF USER SENSOR DATA 审中-公开

    公开(公告)号：US20240177815A1

    公开(公告)日：2024-05-30

    申请号：US18059570

    申请日：2022-11-29

    Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATION

    Inventor： Erhan Bilal ,  Tian Hao ,  Bing Dang ,  Bo Wen ,  Jeffrey L. Rogers

    IPC: G16H10/60

    CPC classification number: G16H10/60

    Abstract: Automated labeling of user sensor data is provided. It is determined that a user is at a medical facility using a location of a user device. User sensor data is collected from one or more user devices while the user is at the medical facility. A result is retrieved of a medical evaluation of the user performed at the medical facility. User sensor data collected during the medical evaluation is tagged with the retrieved result from the medical evaluation.

    REMOTE CONCURRENT ASSESSMENT OF FUNCTIONAL MOBILITY AND WORKING MEMORY
    6.
    发明申请
    REMOTE CONCURRENT ASSESSMENT OF FUNCTIONAL MOBILITY AND WORKING MEMORY 有权

    公开(公告)号：US20240371484A1

    公开(公告)日：2024-11-07

    申请号：US18311924

    申请日：2023-05-04

    Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATION

    Inventor： Bo Wen ,  Erhan Bilal ,  Jenna Reinen

    IPC: G16H20/00 ,  G16H40/67 ,  G16H50/20

    Abstract: A method, computer system, and a computer program product are provided for testing functional mobility and memory. Information is about a participant to an artificial intelligence (AI) engine and then instructions are provided to the participant to memorize a random set of steps. The participant is then asked to recall the random set of instruction steps and then to perform the steps memorized. The participant is asked to recall the steps again after the physical performance. The result of the test is analyzed and a final participant assessment is rendered based on the overall performance analysis. The participant is provided instructions and further monitored and recorded for the performance of the test using smart devices, video or similar means.

    Evaluation of predictions in the absence of a known ground truth
    8.
    发明授权
    Evaluation of predictions in the absence of a known ground truth 有权
    在没有已知地面实况的情况下评估预测

    公开(公告)号：US09582760B2

    公开(公告)日：2017-02-28

    申请号：US14030575

    申请日：2013-09-18

    Applicant: International Business Machines Corporation

    Inventor： Erhan Bilal ,  Gustavo Stolovitzky

    IPC: G06N5/02 ,  G06F19/00 ,  G05B13/04 ,  G06N5/04

    CPC classification number: G06N5/043 ,  G05B13/048 ,  G06F19/00 ,  G06F19/34 ,  G06N5/022 ,  G06N7/005

    Abstract: Disclosed is a novel system, and method to evaluate a prediction of a possibly unknown outcome out of a plurality of predictions of that outcome. The method begins with accessing a particular prediction of an outcome out of a plurality of predictions of that outcome in which the outcome may be unknown. Next, a subsample of the plurality of predictions of the outcome is accessed. The subsample can possibly include the particular prediction. A consensus prediction of the outcome based on the subsample of the plurality of predictions is determined. A proximity of the particular prediction to the consensus prediction is determined. Each prediction is ranked out of the plurality of predictions in an order of a closest in proximity to the consensus prediction to a farthest in proximity to the consensus prediction.

    Abstract translation: 公开了一种新颖的系统和方法，用于评估对该结果的多个预测中的可能未知结果的预测。 该方法首先从结果的多个预测中访问结果的特定预测开始，其中结果可能是未知的。 接下来，访问结果的多个预测的子样本。 子样本可能包括特定的预测。 确定基于多个预测的子样本的结果的共识预测。 确定特定预测与共有预测的接近度。 每个预测在多个预测中以与共识预测接近的最接近的顺序排列到与共识预测相邻最远的预测。

    Evaluation of predictions in the absence of a known ground truth
    9.
    发明授权
    Evaluation of predictions in the absence of a known ground truth 有权
    在没有已知地面实况的情况下评估预测

    公开(公告)号：US09235808B2

    公开(公告)日：2016-01-12

    申请号：US13827776

    申请日：2013-03-14

    Applicant: International Business Machines Corporation

    Inventor： Erhan Bilal ,  Gustavo Stolovitzky

    IPC: G06N5/02 ,  G06F19/00 ,  G05B13/04 ,  G06N5/04

    CPC classification number: G06N5/043 ,  G05B13/048 ,  G06F19/00 ,  G06F19/34 ,  G06N5/022 ,  G06N7/005

    Abstract: Disclosed is a novel system, and method to evaluate a prediction of a possibly unknown outcome out of a plurality of predictions of that outcome. The method begins with accessing a particular prediction of an outcome out of a plurality of predictions of that outcome in which the outcome may be unknown. Next, a subsample of the plurality of predictions of the outcome is accessed. The subsample can possibly include the particular prediction. A consensus prediction of the outcome based on the subsample of the plurality of predictions is determined. A proximity of the particular prediction to the consensus prediction is determined. Each prediction is ranked out of the plurality of predictions in an order of a closest in proximity to the consensus prediction to a farthest in proximity to the consensus prediction.

    Abstract translation: 公开了一种新颖的系统和方法，用于评估对该结果的多个预测中的可能未知结果的预测。 该方法首先从结果的多个预测中访问结果的特定预测开始，其中结果可能是未知的。 接下来，访问结果的多个预测的子样本。 子样本可能包括特定的预测。 确定基于多个预测的子样本的结果的共识预测。 确定特定预测与共有预测的接近度。 每个预测在多个预测中以与共识预测接近的最接近的顺序排列到与共识预测相邻最远的预测。

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