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    SYSTEMS AND METHODS FOR PROCESSING IMAGES TO DETERMINE IMAGE-BASED COMPUTATIONAL BIOMARKERS FROM LIQUID SPECIMENS
    2.
    发明申请
    SYSTEMS AND METHODS FOR PROCESSING IMAGES TO DETERMINE IMAGE-BASED COMPUTATIONAL BIOMARKERS FROM LIQUID SPECIMENS 有权

    公开(公告)号：US20250166397A1

    公开(公告)日：2025-05-22

    申请号：US19028824

    申请日：2025-01-17

    Applicant: PAIGE.AI, Inc.

    Inventor： Brandon ROTHROCK ,  Jillian SUE ,  Matthew HOULISTON ,  Patricia RACITI ,  Leo GRADY

    IPC: G06V20/69 ,  G06F18/2431 ,  G06N20/00 ,  G06T7/00 ,  G06T7/11 ,  G06T7/194 ,  G16H30/40

    Abstract: A method of using machine learning to output task-specific predictions may include receiving a digitized cytology image of a cytology sample and applying a machine learning model to isolate cells of the digitized cytology image. The machine learning model may include identifying a plurality of sub-portions of the digitized cytology image, identifying, for each sub-portion of the plurality of sub-portions, either background or cell, and determining cell sub-images of the digitized cytology image. Each cell sub-image may comprise a cell of the digitized cytology image, based on the identifying either background or cell. The method may further comprise determining a plurality of features based on the cell sub-images, each of the cell sub-images being associated with at least one of the plurality of features, determining an aggregated feature based on the plurality of features, and training a machine learning model to predict a target task based on the aggregated feature.

    SYSTEMS AND METHODS FOR PROCESSING IMAGES TO DETERMINE IMAGE-BASED COMPUTATIONAL BIOMARKERS FROM LIQUID SPECIMENS
    4.
    发明申请
    SYSTEMS AND METHODS FOR PROCESSING IMAGES TO DETERMINE IMAGE-BASED COMPUTATIONAL BIOMARKERS FROM LIQUID SPECIMENS 有权

    公开(公告)号：US20220139533A1

    公开(公告)日：2022-05-05

    申请号：US17511871

    申请日：2021-10-27

    Applicant: PAIGE.AI, Inc.

    Inventor： Brandon ROTHROCK ,  Jillian SUE ,  Matthew HOULISTON ,  Patricia RACITI ,  Leo GRADY

    IPC: G16H30/40 ,  G06N20/00 ,  G06T7/00 ,  G06V20/69 ,  G06T7/194

    Abstract: A method of using a machine learning model to output a task-specific prediction may include receiving a digitized cytology image of a cytology sample and applying a machine learning model to isolate cells of the digitized cytology image. The machine learning model may include identifying a plurality of sub-portions of the digitized cytology image, identifying, for each sub-portion of the plurality of sub-portions, either background or cell, and determining cell sub-images of the digitized cytology image. Each cell sub-image may comprise a cell of the digitized cytology image, based on the identifying either background or cell. The method may further comprise determining a plurality of features based on the cell sub-images, each of the cell sub-images being associated with at least one of the plurality of features, determining an aggregated feature based on the plurality of features, and training a machine learning model to predict a target task based on the aggregated feature.

    SYSTEMS AND METHODS FOR PROCESSING IMAGES TO DETERMINE IMAGE-BASED COMPUTATIONAL BIOMARKERS FROM LIQUID SPECIMENS
    5.
    发明申请
    SYSTEMS AND METHODS FOR PROCESSING IMAGES TO DETERMINE IMAGE-BASED COMPUTATIONAL BIOMARKERS FROM LIQUID SPECIMENS 有权

    公开(公告)号：US20220138450A1

    公开(公告)日：2022-05-05

    申请号：US17519847

    申请日：2021-11-05

    Applicant: PAIGE.AI, Inc.

    Inventor： Brandon ROTHROCK ,  Jillian SUE ,  Matthew HOULISTON ,  Patricia RACITI ,  Leo GRADY

    IPC: G06K9/00 ,  G06T7/11 ,  G06N20/00 ,  G06K9/62

    Abstract: A method of using a machine learning model to output a task-specific prediction may include receiving a digitized cytology image of a cytology sample and applying a machine learning model to isolate cells of the digitized cytology image. The machine learning model may include identifying a plurality of sub-portions of the digitized cytology image, identifying, for each sub-portion of the plurality of sub-portions, either background or cell, and determining cell sub-images of the digitized cytology image. Each cell sub-image may comprise a cell of the digitized cytology image, based on the identifying either background or cell. The method may further comprise determining a plurality of features based on the cell sub-images, each of the cell sub-images being associated with at least one of the plurality of features, determining an aggregated feature based on the plurality of features, and training a machine learning model to predict a target task based on the aggregated feature.

    SYSTEMS AND METHODS TO PROCESS ELECTRONIC IMAGES TO IDENTIFY DIAGNOSTIC TESTS
    7.
    发明申请
    SYSTEMS AND METHODS TO PROCESS ELECTRONIC IMAGES TO IDENTIFY DIAGNOSTIC TESTS 有权

    公开(公告)号：US20220130547A1

    公开(公告)日：2022-04-28

    申请号：US17519834

    申请日：2021-11-05

    Applicant: PAIGE.AI, Inc.

    Inventor： Leo GRADY ,  Christopher KANAN ,  Jorge Sergio REIS-FILHO ,  Belma DOGDAS ,  Matthew HOULISTON

    IPC: G16H50/20 ,  G16H30/40

    Abstract: Systems and methods are disclosed for processing digital images to identify diagnostic tests, the method comprising receiving one or more digital images associated with a pathology specimen, determining a plurality of diagnostic tests, applying a machine learning system to the one or more digital images to identify any prerequisite conditions for each of the plurality of diagnostic tests to be applicable, the machine learning system having been trained by processing a plurality of training images, identifying, using the machine learning system, applicable diagnostic tests of the plurality of diagnostic tests based on the one or more digital images and the prerequisite conditions, and outputting the applicable diagnostic tests to a digital storage device and/or display.

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