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    Image retention and stitching for minimal-flash eye disease diagnosis
    13.
    发明专利
    Image retention and stitching for minimal-flash eye disease diagnosis 未知

    公开(公告)号：AU2021238305A1

    公开(公告)日：2022-11-17

    申请号：AU2021238305

    申请日：2021-03-15

    Applicant: DIGITAL DIAGNOSTICS INC

    Inventor： CLARIDA WARREN JAMES ,  AMELON RYAN EARL ROHRET ,  SHAH ABHAY ,  SUTHER JACOB PATRICK ,  NIEMEIJER MEINDERT ,  ABRAMOFF MICHAEL DAVID

    IPC: A61B3/10

    Abstract: Systems and methods are provided herein for minimizing retinal exposure to flash during image gathering for diagnosis. In an embodiment, a system captures a plurality of retinal images of different retinal regions. The system determines that a first portion of a first image does not meet a criterion while a second portion of the first image does meet the criterion, identifies a portion of the retina depicted in the first portion that does not meet the criterion, and determines whether the portion of the retina is depicted in a third portion of a second image and whether the third portion meets the criterion. Responsive to determining that the third portion meets the criterion, the system performs the diagnosis. Responsive to determining that the portion of the retina is not depicted in the second image, the system captures an additional image of the retinal region.

    DIAGNOSING SKIN CONDITIONS USING MACHINE-LEARNED MODELS
    14.
    发明专利
    DIAGNOSING SKIN CONDITIONS USING MACHINE-LEARNED MODELS 未知

    公开(公告)号：CA3141644A1

    公开(公告)日：2021-01-07

    申请号：CA3141644

    申请日：2020-06-30

    Applicant: DIGITAL DIAGNOSTICS INC

    Inventor： FERRANTE JOSEPH ,  SWART ELLIOT

    IPC: G06N20/00 ,  G06T7/00 ,  G06T7/11 ,  G16H30/00 ,  G16H30/20 ,  G16H30/40

    Abstract: A diagnosis system trains a set of machine-learned diagnosis models that are configured to receive an image of a patient and generate predictions on whether the patient has one or more health conditions. In one embodiment, the set of machine-learned models are trained to generate predictions for images that contain two or more underlying health conditions of the patient. In one instance, the symptoms for the two or more health conditions are shown as two or more overlapping skin abnormalities on the patient. By using the architectures of the set of diagnosis models described herein, the diagnosis system can generate more accurate predictions for images that contain overlapping symptoms for two or more health conditions compared to existing systems.

    Using a set of machine learning diagnostic models to determine a diagnosis based on a skin tone of a patient
    16.
    发明专利
    Using a set of machine learning diagnostic models to determine a diagnosis based on a skin tone of a patient 未知

    公开(公告)号：IL288988D0

    公开(公告)日：2022-02-01

    申请号：IL28898821

    申请日：2021-12-14

    Applicant: DIGITAL DIAGNOSTICS INC

    IPC: G06N20/00 ,  G16H30/40 ,  G16H40/67 ,  G16H50/20

    Abstract: Systems and methods are disclosed herein for determining a diagnosis based on a base skin tone of a patient. In an embodiment, the system receives a base skin tone image of a patient, generates a calibrated base skin tone image by calibrating the base skin tone image using a reference calibration profile, and determines a base skin tone of the patient based on the calibrated base skin tone image. The system receives a concern image of a portion of the patient's skin, and selects a set of machine learning diagnostic models from a plurality of sets of candidate machine learning diagnostic models based on the base skin tone of the patient, each of the sets of candidate machine learning diagnostic models trained to receive the concern image and output a diagnosis of a condition of the patient.

    Diagnosing skin conditions using machine-learned models
    17.
    发明专利
    Diagnosing skin conditions using machine-learned models 未知

    公开(公告)号：IL288866D0

    公开(公告)日：2022-02-01

    申请号：IL28886621

    申请日：2021-12-09

    Applicant: DIGITAL DIAGNOSTICS INC

    IPC: G16H30/40 ,  G16H50/20 ,  G16H50/70

    Abstract: A diagnosis system trains a set of machine-learned diagnosis models that are configured to receive an image of a patient and generate predictions on whether the patient has one or more health conditions. In one embodiment, the set of machine-learned models are trained to generate predictions for images that contain two or more underlying health conditions of the patient. In one instance, the symptoms for the two or more health conditions are shown as two or more overlapping skin abnormalities on the patient. By using the architectures of the set of diagnosis models described herein, the diagnosis system can generate more accurate predictions for images that contain overlapping symptoms for two or more health conditions compared to existing systems.

    MONITORING SURFACE CLEANING OF MEDICAL SURFACES USING VIDEO STREAMING
    18.
    发明专利
    MONITORING SURFACE CLEANING OF MEDICAL SURFACES USING VIDEO STREAMING 未知

    公开(公告)号：CA3145430A1

    公开(公告)日：2020-12-30

    申请号：CA3145430

    申请日：2020-06-26

    Applicant: DIGITAL DIAGNOSTICS INC

    Inventor： FERRANTE JOSEPH ,  GROSS KELSEY J ,  SWART ELLIOT

    IPC: A61L2/24 ,  A47K7/04 ,  A61B90/80 ,  B08B7/04 ,  G08B21/24 ,  G16H40/20

    Abstract: A cleaning wizard monitors and provides feedback for cleaning of medical equipment to ensure that cleaning is performed based on best practices. The cleaning wizard receives a video stream comprising an item of medical equipment and inputs a first set of video frames from the video stream into a first machine learning model. The first machine learning model is trained to output whether the first set of video frames corresponds to activity that initiates a cleaning protocol for the item of medical equipment. Responsive to the cleaning protocol being initiated, the cleaning wizard inputs a second set of video frames into a second machine learning model trained to output whether the second set of frames meets criteria of the cleaning protocol. Responsive to all criteria of the cleaning protocol being met, the cleaning wizard transmits a notification to an operator that the cleaning protocol is complete.

    DIRECT MEDICAL TREATMENT PREDICTIONS USING ARTIFICIAL INTELLIGENCE
    19.
    发明公开
    DIRECT MEDICAL TREATMENT PREDICTIONS USING ARTIFICIAL INTELLIGENCE 审中-公开

    公开(公告)号：US20240347159A1

    公开(公告)日：2024-10-17

    申请号：US18757298

    申请日：2024-06-27

    Applicant: Digital Diagnostics Inc.

    Inventor： Michael D. Abramoff

    IPC: G16H20/00 ,  G06F18/214 ,  G06T7/00 ,  G16H50/20

    CPC classification number: G16H20/00 ,  G06F18/214 ,  G06T7/0012 ,  G16H50/20

    Abstract: A device is disclosed herein that receives image data corresponding to an anatomy of a patient. The device applies the image data to one or more feature models trained using training data that pairs anatomical images to an anatomical feature label, and receives, as output from the one or more feature models, scores for each of a plurality of anatomical features corresponding to the image data. The device applies the scores as input to a treatment model, the treatment model trained to output a prediction of a measure of efficacy of a particular treatment based on features of the patient's anatomy. The device receives, as output from the treatment model, data representative of the predicted measure of efficacy of the particular treatment.

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