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公开(公告)号：US20220238225A1
公开(公告)日：2022-07-28
申请号：US17321734
申请日：2021-05-17
Applicant: Google LLC
Inventor： Marcin Tomasz Sieniek , Sunny Jansen , Krishnan Eswaran , Shruthi Prabhakara , Daniel Shing Shun Tse , Scott Mayer McKinney
Abstract: Systems and methods for artificial intelligence enabled instant diagnostic follow-up can provide efficiency to the medical diagnosis process by providing multiple examinations in the same medical visit for medical workflows that previously required multiple visits. The systems and methods can provide further medical benefit by implementing triaging systems to ensure the most urgent cases are seen immediately.
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Patent Agency Ranking
公开(公告)号：US11126649B2
公开(公告)日：2021-09-21
申请号：US16032276
申请日：2018-07-11
Applicant: Google LLC
Inventor： Krishnan Eswaran , Shravya Shetty , Daniel Shing Shun Tse , Shahar Jamshy , Zvika Ben-Haim
Abstract: A computer-implemented system is described for identifying and retrieving similar radiology images to a query image. The system includes one or more fetchers receiving the query image and retrieving a set of candidate similar radiology images from a data store. One or more scorers receive the query image and the set of candidate similar radiology images and generate a similarity score between the query image and each candidate image. A pooler receives the similarity scores from the one or more scorers, ranks the candidate images, and returns a list of the candidate images reflecting the ranking. The scorers implement a modelling technique to generate the similarity score capturing a plurality of similarity attributes of the query image and the set of candidate similar radiology images and annotations associated therewith. For example, the similarity attributes could be patient, diagnostic and/or visual similarity, and the modelling techniques could be triplet loss, classification loss, regression loss and object detection loss.
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3.发明申请公开(公告)号：US20200152302A1
公开(公告)日：2020-05-14
申请号：US16612879
申请日：2017-10-20
Applicant: Google LLC
Inventor： Christopher Co , Gang Li , Philip Chung , Justin Paul , Daniel Shing Shun Tse , Katherine Chou , Diana Jaunzeikare , Alvin Rajkomar
Abstract: A method and system is provided for assisting a user to assign a label to words or spans of text in a transcript of a conversation between a patient and a medical professional and form groupings of such labelled words or spans of text in the transcript. The transcript is displayed on an interface of a workstation. A tool is provided for highlighting spans of text in the transcript consisting of one or more words. Another tool is provided for assigning a label to the highlighted spans of text. This tool includes a feature enabling searching through a set of predefined labels available for assignment to the highlighted span of text. The predefined labels encode medical entities and attributes of the medical entities. The interface further includes a tool for creating groupings of related highlighted spans of texts. The tools can consist of mouse action or key strokes or a combination thereof.
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4.发明申请公开(公告)号：US20230055094A1
公开(公告)日：2023-02-23
申请号：US17978790
申请日：2022-11-01
Applicant: Google LLC
Inventor： Christopher Co , Gang Li , Philip Chung , Justin Paul , Daniel Shing Shun Tse , Katherine Chou , Diana Jaunzeikare , Alvin Rajkomar
Abstract: A method and system is provided for assisting a user to assign a label to words or spans of text in a transcript of a conversation between a patient and a medical professional and form groupings of such labelled words or spans of text in the transcript. The transcript is displayed on an interface of a workstation. A tool is provided for highlighting spans of text in the transcript consisting of one or more words. Another tool is provided for assigning a label to the highlighted spans of text. This tool includes a feature enabling searching through a set of predefined labels available for assignment to the highlighted span of text. The predefined labels encode medical entities and attributes of the medical entities. The interface further includes a tool for creating groupings of related highlighted spans of texts. The tools can consist of mouse action or keystrokes or a combination thereof.
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5.发明授权公开(公告)号：US11521722B2
公开(公告)日：2022-12-06
申请号：US16612879
申请日：2017-10-20
Applicant: Google LLC
Inventor： Christopher Co , Gang Li , Philip Chung , Justin Paul , Daniel Shing Shun Tse , Katherine Chou , Diana Jaunzeikare , Alvin Rajkomar
Abstract: A method and system is provided for assisting a user to assign a label to words or spans of text in a transcript of a conversation between a patient and a medical professional and form groupings of such labelled words or spans of text in the transcript. The transcript is displayed on an interface of a workstation. A tool is provided for highlighting spans of text in the transcript consisting of one or more words. Another tool is provided for assigning a label to the highlighted spans of text. This tool includes a feature enabling searching through a set of predefined labels available for assignment to the highlighted span of text. The predefined labels encode medical entities and attributes of the medical entities. The interface further includes a tool for creating groupings of related highlighted spans of texts. The tools can consist of mouse action or key strokes or a combination thereof.
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公开(公告)号：US20200019617A1
公开(公告)日：2020-01-16
申请号：US16032276
申请日：2018-07-11
Applicant: Google LLC
Inventor： Krishnan Eswaran , Shravya Shetty , Daniel Shing Shun Tse , Shahar Jamshy , Zvika Ben-Haim
Abstract: A computer-implemented system is described for identifying and retrieving similar radiology images to a query image. The system includes one or more fetchers receiving the query image and retrieving a set of candidate similar radiology images from a data store. One or more scorers receive the query image and the set of candidate similar radiology images and generate a similarity score between the query image and each candidate image. A pooler receives the similarity scores from the one or more scorers, ranks the candidate images, and returns a list of the candidate images reflecting the ranking. The scorers implement a modelling technique to generate the similarity score capturing a plurality of similarity attributes of the query image and the set of candidate similar radiology images and annotations associated therewith. For example, the similarity attributes could be patient, diagnostic and/or visual similarity, and the modelling techniques could be triplet loss, classification loss, regression loss and object detection loss.
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