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    LOCATION-BASED MEDICAL SCAN ANALYSIS SYSTEM
    47.
    发明申请
    LOCATION-BASED MEDICAL SCAN ANALYSIS SYSTEM 审中-公开

    公开(公告)号：US20200161005A1

    公开(公告)日：2020-05-21

    申请号：US16365780

    申请日：2019-03-27

    Applicant: Enlitic, Inc.

    Inventor： Kevin Lyman ,  Li Yao ,  Eric C. Poblenz ,  Jordan Prosky ,  Ben Covington ,  Anthony Upton

    IPC: G16H50/70 ,  G16H30/40 ,  G06N5/04

    Abstract: A location-based medical scan analysis system is operable to generate a generic model by performing a training step on image data of a plurality of medical scans. Location-based subsets of the plurality of medical scans are generated by including ones of the plurality of medical scans with originating locations that compare favorably to location grouping criteria for the each location-based subset. A plurality of location-based models are generated by performing a fine-tuning step on the generic model, utilizing a corresponding one of the plurality of location-based subsets. Inference data is generated for a new medical scan by utilizing one of the location-based models on the new medical scan, where an originating location associated with the new medical scan compares favorably to location grouping criteria for the location-based subset utilized to generate the location-based model. The inference data is transmitted to a client device for display via a display device.

    UTILIZING MULTIPLE SUB-MODELS VIA A MULTI-MODEL MEDICAL SCAN ANALYSIS SYSTEM
    48.
    发明申请
    UTILIZING MULTIPLE SUB-MODELS VIA A MULTI-MODEL MEDICAL SCAN ANALYSIS SYSTEM 审中-公开

    公开(公告)号：US20200160971A1

    公开(公告)日：2020-05-21

    申请号：US16365772

    申请日：2019-03-27

    Applicant: Enlitic, Inc.

    Inventor： Kevin Lyman ,  Li Yao ,  Eric C. Poblenz ,  Jordan Prosky ,  Ben Covington ,  Anthony Upton

    IPC: G16H30/20 ,  G06T7/00 ,  A61B5/00 ,  G06T7/11 ,  G16H10/60

    Abstract: A multi-model medical scan analysis system is operable to generate a plurality of training sets from a plurality of medical scans. Each of a set of sub-models can be generated by performing a training step on a corresponding one of the plurality of training sets. A subset of the set of sub-models is selected for a new medical scan. A set of abnormality data is generated by applying a subset of a set of inference functions on the new medical scan, where the subset of the set of inference functions utilize the subset of the set of sub-models. Final abnormality data is generated by performing a final inference function on the set of abnormality data. The final abnormality data can be to a client device for display via a display device.

    PEER-REVIEW FLAGGING SYSTEM
    49.
    发明申请
    PEER-REVIEW FLAGGING SYSTEM 审中-公开

    公开(公告)号：US20200160954A1

    公开(公告)日：2020-05-21

    申请号：US16359258

    申请日：2019-03-20

    Applicant: Enlitic, Inc.

    Inventor： Kevin Lyman ,  Anthony Upton ,  Li Yao ,  Ben Covington

    IPC: G16H15/00 ,  G16H30/20 ,  G06N5/04 ,  G06N20/00 ,  G06F9/54

    Abstract: A peer-review flagging system is operable to receive a medical scan and a medical report written by a medical professional in conjunction with review of the medical scan. Automated assessment data is generated by performing an inference function on the medical scan by utilizing a computer vision model trained on a plurality of medical scans. Human assessment data is generated by performing an extraction function on the medical report. Consensus data is generated by comparing the automated assessment data to the first human assessment data. A peer-review notification is transmitted to a client device for display. The peer-review notification indicates the medical scan is flagged for peer-review in response to determining the consensus data indicates the automated assessment data compares unfavorably to the human assessment data.

    FINE-TUNING A GENERIC MODEL VIA A MULTI-MODEL MEDICAL SCAN ANALYSIS SYSTEM
    50.
    发明申请
    FINE-TUNING A GENERIC MODEL VIA A MULTI-MODEL MEDICAL SCAN ANALYSIS SYSTEM 审中-公开

    公开(公告)号：US20200160520A1

    公开(公告)日：2020-05-21

    申请号：US16365794

    申请日：2019-03-27

    Applicant: Enlitic, Inc.

    Inventor： Jordan Prosky ,  Li Yao ,  Eric C. Poblenz ,  Kevin Lyman ,  Ben Covington ,  Anthony Upton

    IPC: G06T7/00 ,  G06K9/62 ,  G16H30/20 ,  G16H30/40

    Abstract: A multi-model medical scan analysis system is operable to generate a generic model by performing a training step on image data of a plurality of medical scans and corresponding labeling data. A plurality of fine-tuned models corresponding to one of a plurality of abnormality types can be generated by performing a fine-tuning step on the generic model. Abnormality detection data can be generated for a new medical scan by performing utilizing the generic model. One of the plurality of abnormality types is determined to be detected in the new medical scan based on the abnormality detection data, and a fine-tuned model that corresponds to the abnormality type is selected. Additional abnormality data is generated for the new medical scan by utilizing the selected fine-tuned model. The additional abnormality data can be transmitted to a client device for display via a display device.

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