Automatic clinical report generation

    公开(公告)号:US11848100B2

    公开(公告)日:2023-12-19

    申请号:US16657506

    申请日:2019-10-18

    Abstract: Methods and systems for clinical report generation. One system includes an electronic processor configured to receive a query image and determine a similarity metric for a plurality of medical images, where the similarity metric represents a similarity between the query image and each of the plurality of medical images. The electronic processor is also configured to determine a predetermined number of medical images from the plurality of medical images based on the similarity metric for each of the plurality of medical images. The electronic processor is also configured to rank a plurality of reports, where each of the plurality of reports correspond to one of the predetermined number of medical images. The electronic processor is also configured to generate a clinical report including information extracted from at least one of the plurality of reports based on the ranking of the plurality of reports.

    MEDICAL IMAGE STUDY DIFFICULTY ESTIMATION
    3.
    发明公开

    公开(公告)号:US20230214994A1

    公开(公告)日:2023-07-06

    申请号:US17569465

    申请日:2022-01-05

    Abstract: Methods and systems for assigning a medical image study for review. One method includes receiving a plurality of labeled medical image studies and one or more prior image studies of a patient associated with each of plurality of labeled medical image studies. The method also includes creating a set of training data including the plurality of labeled medical image studies and the one or more prior image studies received for each of the plurality of labeled medical image studies and training an artificial intelligence (AI) system using the set of training data. In addition, the method includes estimating, using the AI system as trained, a difficulty metric for an unlabeled medical image study based on the unlabeled medical image study and one or more prior image studies of a patient associated with the unlabeled image study and assigning the unlabeled medical image study for review based on the difficulty metric.

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