DETECTING NEURALLY PROGRAMMED TUMORS USING EXPRESSION DATA

    公开(公告)号:US20220262458A1

    公开(公告)日:2022-08-18

    申请号:US17629327

    申请日:2020-07-24

    Abstract: Embodiments disclosed herein generally relate to classifying a tumor, based on gene expression data, as being neurally related or non-neurally related. The tumor may be classified using a machine-learning model, which may have been trained to differentiate gene-expression data associated with neuronal or neuroendocrine tumors from gene-expression data associated with non-neuronal and non-neuroendocrine tumors. Differential treatment and/or treatment recommendations may be provided based on the classification. First-line checkpoint blockade therapy may be used or recommended when a tumor is identified as being non-neurally related, and a combination therapy (e.g., initial chemotherapy and subsequent checkpoint blockade therapy) may be used or recommended when a tumor is identified as being neurally related.

    THREE-DIMENSIONAL OBJECT SEGMENTATION OF MEDICAL IMAGES LOCALIZED WITH OBJECT DETECTION

    公开(公告)号:US20220230310A1

    公开(公告)日:2022-07-21

    申请号:US17665932

    申请日:2022-02-07

    Abstract: The present disclosure relates to techniques for segmenting objects within medical images using a deep learning network that is localized with object detection based on a derived contrast mechanism. Particularly, aspects are directed to localizing an object of interest within a first medical image having a first characteristic, projecting a bounding box or segmentation mask of the object of interest onto a second medical image having a second characteristic to define a portion of the second medical image, and inputting the portion of the second medical image into a deep learning model that is constructed as a detector using a weighted loss function capable of segmenting the portion of the second medical image and generating a segmentation boundary around the object of interest. The segmentation boundary may be used to calculate a volume of the object of interest for determining a diagnosis and/or a prognosis of a subject.

    METHODS FOR DIAGNOSING AND TREATING INFLAMMATORY BOWEL DISEASE

    公开(公告)号:US20220186314A1

    公开(公告)日:2022-06-16

    申请号:US17580357

    申请日:2022-01-20

    Abstract: Biomarkers predictive of responsiveness to integrin beta7 antagonists, including anti-beta7 integrin subunit antibodies, and methods of using such biomarkers are provided. In addition, methods of treating gastrointestinal inflammatory disorders such as inflammatory bowel diseases including ulcerative colitis and Crohn's disease are provided. Also provided are methods of using such predictive biomarkers for the treatment of inflammatory bowel diseases including ulcerative colitis and Crohn's disease.

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