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510(k) Data Aggregation

    K Number
    K183478
    Device Name
    ClearON Mobile
    Manufacturer
    Rayence Co.,Ltd
    Date Cleared
    2019-03-01

    (74 days)

    Product Code
    LLZ
    Regulation Number
    892.2050
    Type
    Special
    Panel
    Radiology (RA)
    Reference & Predicate Devices
    K160579
    Why did this record match?
    Device Name :

    ClearON Mobile

    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    Clear On Mobile software carries out the image processing and administration of medical X-ray data which includes adjustment of window leveling, rotation, zoom, and measurements. Clear on Mobel is not approved for mammography and is meant to be used by qualified medical personnel only. Clear On Mobile is complying with DICOM standards to assure optimum communications between network systems.

    Device Description

    ClearON Mobile provides easy touch based user interface to perform diagnosis of digital radiograph images displayed on ClearOn Mobile. ClearON Mobile receives digital images from a flat panel detector and a X-ray generator. The software also manages patient data, stores and transfers diagnostic images in an internal database.

    It supports DICOM image file format which allows interoperability with other Radiography equipment in network environment.

    AI/ML Overview

    The provided text is a 510(k) summary for the ClearON Mobile software. It describes the device, its functions, and a comparison to a predicate device. However, it does not contain information about an acceptance criteria table, reported device performance metrics, sample sizes (for test or training sets), data provenance, number or qualifications of experts establishing ground truth, adjudication methods, multi-reader multi-case studies, standalone performance, or the specific type of ground truth used.

    The document only states that "The validation testing verified and validated the risk analysis and individual performance results were within the predetermined acceptance criteria." but does not elaborate on what those criteria were or what the performance results specifically were.

    Therefore, I cannot fulfill the request to provide the detailed information about acceptance criteria and the study that proves the device meets them based on the input provided.

    The document primarily focuses on demonstrating substantial equivalence to a predicate device by comparing features and stating that the pre and post image processing algorithms are identical. It does not present a performance study with detailed metrics against defined acceptance criteria.

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