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公开(公告)号：US10922628B2
公开(公告)日：2021-02-16
申请号：US16684627
申请日：2019-11-15
Applicant: Lunit Inc.
Inventor： Dong Geun Yoo , Kyung Hyun Paeng , Sung Gyun Park
Abstract: A machine learning method that may reduce an annotation cost and may improve performance of a target model is provided. Some embodiments of the present disclosure may provide a machine learning method performed by a computing device, including: acquiring a training dataset of a first model including a plurality of data samples to which label information is not given; calculating a miss-prediction probability of the first model on the plurality of data samples; configuring a first data sample group by selecting at least one data sample from the plurality of data samples based on the calculated miss-prediction probability; acquiring first label information on the first data sample group; and performing first learning on the first model by using the first data sample group and the first label information.
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公开(公告)号：US20250069420A1
公开(公告)日：2025-02-27
申请号：US18946457
申请日：2024-11-13
Applicant: Lunit Inc.
Inventor： Biagio BRATTOLI , Chan-Young Ock , Wonkyung Jung , Soo Ick Cho , Kyunghyun Paeng , Dong Geun Yoo
Abstract: Provided is a method for analysing a pathology image, which is performed by at least one processor and includes acquiring a pathology image, inputting the acquired pathology image into a machine learning model and acquiring an analysis result for the pathology image from the machine learning model, and outputting the acquired analysis result, in which the machine learning model is a model trained by using a training data set generated based on a first pathology data set associated with a first domain and a second pathology data set associated with a second domain different from the first domain.
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Patent Agency Ranking
公开(公告)号：US12136483B2
公开(公告)日：2024-11-05
申请号：US18627705
申请日：2024-04-05
Applicant: Lunit Inc.
Inventor： Jong Chan Park , Dong Geun Yoo , Ki Hyun You , Hyeon Seob Nam , Hyun Jae Lee , Sang Hyup Lee
IPC: G16H30/20 , G06T7/00 , G06V30/166 , G16H30/40
Abstract: The present disclosure relates to a medical image analysis method using a processor and a memory which are hardware. The method includes generating predicted second metadata for a medical image by using a prediction model, and determining a processing method of the medical image based on one of first metadata stored corresponding to the medical image and the second metadata.
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公开(公告)号：US11967076B2
公开(公告)日：2024-04-23
申请号：US18122837
申请日：2023-03-17
Applicant: LUNIT INC.
Inventor： Jeong Seok Kang , Dong Geun Yoo , Soo Ick Cho , Won Kyung Jung
CPC classification number: G06T7/0012 , G06F3/14 , G06V10/761 , G16H15/00 , G16H50/20 , G06T2207/20081 , G06T2207/30024
Abstract: A computing device includes at least one memory, and at least one processor configured to generate, based on first analysis on a pathological slide image, first biomarker expression information, generate, based on a user input for updating at least some of results of the first analysis, second biomarker expression information about the pathological slide image, and control a display device to output a report including medical information about at least some regions included in the pathological slide image, based on at least one of the first biomarker expression information or the second biomarker expression information.
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公开(公告)号：US12266196B2
公开(公告)日：2025-04-01
申请号：US18491314
申请日：2023-10-20
Applicant: Lunit Inc.
Inventor： Biagio Brattoli , Chan-Young Ock , Wonkyung Jung , Soo Ick Cho , Kyunghyun Paeng , Dong Geun Yoo
Abstract: Provided is a method for analysing a pathology image, which is performed by at least one processor and includes acquiring a pathology image, inputting the acquired pathology image into a machine learning model and acquiring an analysis result for the pathology image from the machine learning model, and outputting the acquired analysis result, in which the machine learning model is a model trained by using a training data set generated based on a first pathology data set associated with a first domain and a second pathology data set associated with a second domain different from the first domain.
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公开(公告)号：US11978548B2
公开(公告)日：2024-05-07
申请号：US17426336
申请日：2020-05-22
Applicant: Lunit Inc.
Inventor： Jong Chan Park , Dong Geun Yoo , Ki Hyun You , Hyeon Seob Nam , Hyun Jae Lee , Sang Hyup Lee
IPC: G16H30/20 , G06F18/214 , G06N20/00 , G06T7/00 , G06T7/70 , G06V10/70 , G06V30/166 , G16H30/40
CPC classification number: G16H30/20 , G06F18/214 , G06N20/00 , G06T7/0012 , G06T7/70 , G06V10/70 , G06V30/166 , G16H30/40 , G06T2207/20081 , G06T2207/20084 , G06T2207/30004
Abstract: The present disclosure relates to a medical image analysis method using a processor and a memory which are hardware. The method includes generating predicted second metadata for a medical image by using a prediction model, and determining a processing method of the medical image based on one of first metadata stored corresponding to the medical image and the second metadata.
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公开(公告)号：US11875893B2
公开(公告)日：2024-01-16
申请号：US18102465
申请日：2023-01-27
Applicant: LUNIT INC.
Inventor： Jeong Seok Kang , Jae Hong Aum , Dong Geun Yoo , Tai Won Chung
Abstract: A computing apparatus includes: at least one memory; and at least one processor, wherein the processor generates quantitative information regarding at least one cell included in a region of interest of a pathological slide image by analyzing the pathological slide image, generates qualitative information regarding at least one tissue included in the pathological slide image by analyzing the pathological slide image, and controls a display apparatus to output at least one of the quantitative information and the qualitative information on the pathological slide image according to a manipulation of a user.
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