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1.发明申请公开(公告)号：US20210279611A1
公开(公告)日：2021-09-09
申请号：US17303164
申请日：2021-05-21
Applicant: PAIGE.AI, Inc.
Inventor： Supriya KAPUR , Christopher KANAN , Thomas FUCHS , Leo GRADY
Abstract: Systems and methods are disclosed for receiving a target image corresponding to a target specimen, the target specimen comprising a tissue sample of a patient, applying a machine learning model, which may also be known as a machine learning system, to the target image to determine at least one characteristic of the target specimen and/or at least one characteristic of the target image, the machine learning model having been generated by processing a plurality of training images to predict at least one characteristic, the training images comprising images of human tissue and/or images that are algorithmically generated, and outputting the at least one characteristic of the target specimen and/or the at least one characteristic of the target image.
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2.发明公开公开(公告)号：US20230144137A1
公开(公告)日：2023-05-11
申请号：US18149969
申请日：2023-01-04
Applicant: PAIGE.AI, Inc.
Inventor： Supriya KAPUR , Christopher KANAN , Thomas FUCHS , Leo GRADY
CPC classification number: G06N5/04 , G06N20/00 , G06T7/0012 , G06T2207/20076 , G06T2207/20081 , G06T2207/30168
Abstract: Systems and methods are disclosed for receiving a target image corresponding to a target specimen, the target specimen comprising a tissue sample of a patient, applying a machine learning model to the target image to determine at least one characteristic of the target specimen and/or at least one characteristic of the target image, the machine learning model having been generated by processing a plurality of training images to predict at least one characteristic, the training images comprising images of human tissue and/or images that are algorithmically generated, and outputting the at least one characteristic of the target specimen and/or the at least one characteristic of the target image.
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3.发明申请公开(公告)号：US20210117826A1
公开(公告)日：2021-04-22
申请号：US17112435
申请日：2020-12-04
Applicant: PAIGE.AI, Inc.
Inventor： Supriya KAPUR , Christopher KANAN , Thomas FUCHS , Leo GRADY
Abstract: Systems and methods are disclosed for receiving a target image corresponding to a target specimen, the target specimen comprising a tissue sample of a patient, applying a machine learning model, which may also be known as a machine learning system, to the target image to determine at least one characteristic of the target specimen and/or at least one characteristic of the target image, the machine learning model having been generated by processing a plurality of training images to predict at least one characteristic, the training images comprising images of human tissue and/or images that are algorithmically generated, and outputting the at least one characteristic of the target specimen and/or the at least one characteristic of the target image.
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4.发明申请公开(公告)号：US20250165820A1
公开(公告)日：2025-05-22
申请号：US19028442
申请日：2025-01-17
Applicant: PAIGE.AI, Inc.
Inventor： Supriya KAPUR , Christopher KANAN , Thomas FUCHS , Leo GRADY
Abstract: Systems and methods are disclosed for receiving a target image corresponding to a target specimen, the target specimen comprising a tissue sample of a patient, applying a machine learning model to the target image to determine at least one characteristic of the target specimen and/or at least one characteristic of the target image, the machine learning model having been generated by processing a plurality of training images to predict at least one characteristic, the training images comprising images of human tissue and/or images that are algorithmically generated, and outputting the at least one characteristic of the target specimen and/or the at least one characteristic of the target image.
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Patent Agency Ranking
公开(公告)号：US20230245309A1
公开(公告)日：2023-08-03
申请号：US18295577
申请日：2023-04-04
Applicant: PAIGE.AI, Inc.
Inventor： Supriya KAPUR , Ran GODRICH , Christopher KANAN , Thomas FUCHS , Leo GRADY
CPC classification number: G06T7/0012 , G06F18/214 , G06T7/11 , G06V20/695 , G06V20/698 , G16H10/40 , G16H30/40 , G16H50/20 , G06T2207/10056 , G06T2207/20081 , G06T2207/30024 , G06V2201/03
Abstract: Systems and methods are disclosed for receiving a target electronic image corresponding to a target specimen, the target specimen comprising a tissue sample of a patient, applying a machine learning system to the target electronic image to identify a region of interest of the target specimen and determine an expression level of, category of, and/or presence of a biomarker in the region of interest, the biomarker comprising at least one from among an epithelial growth factor receptor (EGFR) biomarker and/or a DNA mismatch repair (MMR) deficiency biomarker, the machine learning system having been generated by processing a plurality of training images to predict whether a region of interest is present in the target electronic image, the training images comprising images of human tissue and/or images that are algorithmically generated, and outputting the determined expression level of, category of, and/or presence of the biomarker in the region of interest.
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6.发明申请公开(公告)号：US20220215277A1
公开(公告)日：2022-07-07
申请号：US17705908
申请日：2022-03-28
Applicant: PAIGE.AI, Inc.
Inventor： Supriya KAPUR , Christopher KANAN , Thomas FUCHS , Leo GRADY
Abstract: Systems and methods are disclosed for receiving a target image corresponding to a target specimen, the target specimen comprising a tissue sample of a patient, applying a machine learning model, which may also be known as a machine learning system, to the target image to determine at least one characteristic of the target specimen and/or at least one characteristic of the target image, the machine learning model having been generated by processing a plurality of training images to predict at least one characteristic, the training images comprising images of human tissue and/or images that are algorithmically generated, and outputting the at least one characteristic of the target specimen and/or the at least one characteristic of the target image.
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7.发明公开公开(公告)号：US20240127086A1
公开(公告)日：2024-04-18
申请号：US18396868
申请日：2023-12-27
Applicant: PAIGE.AI, Inc.
Inventor： Supriya KAPUR , Christopher KANAN , Thomas FUCHS , Leo GRADY
CPC classification number: G06N5/04 , G06N20/00 , G06T7/0012 , G06T2207/20076 , G06T2207/20081 , G06T2207/30168
Abstract: Systems and methods are disclosed for receiving a target image corresponding to a target specimen, the target specimen comprising a tissue sample of a patient, applying a machine learning model to the target image to determine at least one characteristic of the target specimen and/or at least one characteristic of the target image, the machine learning model having been generated by processing a plurality of training images to predict at least one characteristic, the training images comprising images of human tissue and/or images that are algorithmically generated, and outputting the at least one characteristic of the target specimen and/or the at least one characteristic of the target image.
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公开(公告)号：US20220335607A1
公开(公告)日：2022-10-20
申请号：US17810815
申请日：2022-07-05
Applicant: PAIGE.AI, Inc.
Inventor： Supriya KAPUR , Ran GODRICH , Christopher KANAN , Thomas FUCHS , Leo GRADY
Abstract: Systems and methods are disclosed for receiving a target electronic image corresponding to a target specimen, the target specimen comprising a tissue sample of a patient, applying a machine learning system to the target electronic image to identify a region of interest of the target specimen and determine an expression level of, category of, and/or presence of a biomarker in the region of interest, the biomarker comprising at least one from among an epithelial growth factor receptor (EGFR) biomarker and/or a DNA mismatch repair (MMR) deficiency biomarker, the machine learning system having been generated by processing a plurality of training images to predict whether a region of interest is present in the target electronic image, the training images comprising images of human tissue and/or images that are algorithmically generated, and outputting the determined expression level of, category of, and/or presence of the biomarker in the region of interest.
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公开(公告)号：US20210073986A1
公开(公告)日：2021-03-11
申请号：US17016048
申请日：2020-09-09
Applicant: PAIGE.AI, Inc.
Inventor： Supriya KAPUR , Ran GODRICH , Christopher KANAN , Thomas FUCHS , Leo GRADY
Abstract: Systems and methods are disclosed for receiving a target electronic image corresponding to a target specimen, the target specimen comprising a tissue sample of a patient, applying a machine learning system to the target electronic image to identify a region of interest of the target specimen and determine an expression level of, category of, and/or presence of a biomarker in the region of interest, the biomarker comprising at least one from among an epithelial growth factor receptor (EGFR) biomarker and/or a DNA mismatch repair (MMR) deficiency biomarker, the machine learning system having been generated by processing a plurality of training images to predict whether a region of interest is present in the target electronic image, the training images comprising images of human tissue and/or images that are algorithmically generated, and outputting the determined expression level of, category of, and/or presence of the biomarker in the region of interest.
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