公开(公告)号：US11727674B2

公开(公告)日：2023-08-15

申请号：US17549040

申请日：2021-12-13

申请人： TEMPUS LABS, INC.

发明人： Aïcha Bentaieb ,  Martin Christian Stumpe ,  Aly Azeem Khan

IPC分类号： G16C20/70 ,  G06V20/69 ,  G06V10/774

CPC分类号： G06V10/7747 ,  G06V20/698 ,  G16C20/70

摘要： A system and method are provided for training and using a machine learning model to analyze hematoxylin and eosin (H&E) slide images, where the machine learning model is trained using a training data set comprising a plurality of unmarked H&E images and a plurality of marked H&E images, each marked H&E image being associated with one unmarked H&E image and each marked H&E image including a location of one or more molecules determined by analyzing a multiplex IHC image having at least two IHC stains, each IHC stain having a unique color and a unique target molecule. Predicted molecules and locations identified with the machine learning model result in an immunotherapy response class being assigned to the H&E slide image.

公开(公告)号：US20230343074A1

公开(公告)日：2023-10-26

申请号：US18210449

申请日：2023-06-15

申请人： TEMPUS LABS, INC.

发明人： Aïcha Bentaieb ,  Martin Christian Stumpe ,  Aly Azeem Khan

IPC分类号： G06V10/774 ,  G16C20/70 ,  G06V20/69

CPC分类号： G06V10/7747 ,  G16C20/70 ,  G06V20/698

摘要： A system and method are provided for training and using a machine learning model to analyze hematoxylin and eosin (H&E) slide images, where the machine learning model is trained using a training data set comprising a plurality of unmarked H&E images and a plurality of marked H&E images, each marked H&E image being associated with one unmarked H&E image and each marked H&E image including a location of one or more molecules determined by analyzing a multiplex IHC image having at least two IHC stains, each IHC stain having a unique color and a unique target molecule. Predicted molecules and locations identified with the machine learning model result in an immunotherapy response class being assigned to the H&E slide image.

公开(公告)号：US20220189150A1

公开(公告)日：2022-06-16

申请号：US17549040

申请日：2021-12-13

申请人： TEMPUS LABS, INC.

发明人： Aïcha Bentaieb ,  Martin Christian Stumpe ,  Aly Azeem Khan

IPC分类号： G06V10/774 ,  G06V20/69 ,  G16C20/70

摘要： A system and method are provided for training and using a machine learning model to analyze hematoxylin and eosin (H&E) slide images, where the machine learning model is trained using a training data set comprising a plurality of unmarked H&E images and a plurality of marked H&E images, each marked H&E image being associated with one unmarked H&E image and each marked H&E image including a location of one or more molecules determined by analyzing a multiplex IHC image having at least two IHC stains, each IHC stain having a unique color and a unique target molecule. Predicted molecules and locations identified with the machine learning model result in an immunotherapy response class being assigned to the H&E slide image.