CLASSIFICATION MODELS FOR ANALYZING A SAMPLE

    公开(公告)号:US20230026108A1

    公开(公告)日:2023-01-26

    申请号:US17783839

    申请日:2020-12-10

    Abstract: Apparatus and methods are described including analyzing one or more microscopic images of the blood sample using a machine-learning classifier. An entity within the one or more microscopic images is identified using a first classification model, and a first estimated concentration of the entity within the sample is determined, based upon the entity as identified using the first classification model. The entity is identified within the one or more microscopic images using a second classification model, and a second estimated concentration of the entity within the sample is determined, based upon the entity as identified using the second classification model. The first and second estimated concentrations are compared to each other, and, in response to the comparison, a hybrid classification model that is a hybrid of the first and second classification models is used. Other applications are also described.

    DISTINGUISHING BETWEEN BLOOD SAMPLE COMPONENTS

    公开(公告)号:US20200300750A1

    公开(公告)日:2020-09-24

    申请号:US16088321

    申请日:2017-03-23

    Abstract: Apparatus and methods are described for use with an output device (34), and a blood sample (12) that was drawn from a subject. A microscope system (10) acquires first and second images of the blood sample at respective times. A computer processor (28) determines whether, between acquisitions of the first and second images, there was relative motion between at least one erythrocyte within the sample and at least one entity within the sample, by comparing the first and second images to one another. At least partially in response thereto, the computer processor determines whether the entity is an extra-erythrocytic or an intra-erythrocytic entity, and generates an output on the output device, at least partially in response thereto. Other applications are also described.

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