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510(k) Data Aggregation

    K Number
    K142837
    Date Cleared
    2015-01-29

    (121 days)

    Product Code
    Regulation Number
    886.1570
    Reference & Predicate Devices
    Why did this record match?
    Device Name :

    HEINE SIGMA 250 & HEINE SIGMA 250 M2

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

    The HEINE SIGMA® 250 (M2) are battery powered indirect ophthalmoscopes for medical professionals, containing illumination and viewing optics intended to examine the media (cornea, aqueous, lens, vitreous) and the retina of the eye.

    Device Description

    The HEINE SIGMA® 250 (M2) are indirect ophthalmoscopes, worn on the user's head to provide illumination and viewing optics in order to examine the media and the retina of a patient`s eye. The indirect ophthalmoscopes are battery operated.

    AI/ML Overview

    I am sorry, but the provided text does not contain the information required to answer your request. The document is an FDA 510(k) premarket notification for an ophthalmoscope, which is a physical diagnostic device, not an AI/software-based device.

    Therefore, it does not include:

    1. Acceptance criteria or device performance for an AI algorithm.
    2. Sample sizes for test sets, data provenance, or details about training sets.
    3. Information on expert involvement (number, qualifications, adjudication methods) for establishing ground truth.
    4. Details on AI-specific studies like MRMC comparative effectiveness or standalone algorithm performance.
    5. Types of ground truth used in the context of AI models (e.g., pathology, outcomes data).

    The document focuses on demonstrating substantial equivalence to a predicate ophthalmoscope based on intended use, technological characteristics, and safety standards for the physical device. It mentions "non-clinical performance testing" for the ophthalmoscope itself, referring to compliance with ISO standards for optical radiation and fundamental requirements, not the performance of a diagnostic AI.

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