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510(k) Data Aggregation

    K Number
    K180386
    Device Name
    Meron Plus QM
    Manufacturer
    Date Cleared
    2018-05-08

    (85 days)

    Product Code
    Regulation Number
    872.3275
    Panel
    Dental
    Reference & Predicate Devices
    N/A
    Why did this record match?
    Device Name :

    Meron Plus QM

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

    Cementation of: - metal-based inlays, onlays, crowns and bridges - high-strength (zirconia-based) all-ceramic crowns and bridges - metal, ceramic and fiber posts - high strength all ceramic inlays i - । resin inlays, onlays, crowns and bridges

    Device Description

    Not Found

    AI/ML Overview

    I apologize, but the provided text from the FDA 510(k) clearance letter for "Meron Plus OM" does not contain any information about acceptance criteria or a study proving that an AI/ML device meets those criteria.

    The document is a standard clearance letter for a dental cement, outlining its classification, predicate device, and intended uses. It primarily addresses regulatory aspects, not performance studies of an AI/ML system.

    Therefore, I cannot fulfill your request to describe the acceptance criteria and study proving device performance using the provided text.

    To answer your question, I would need a document related to the clearance of an AI/ML-driven medical device, which would typically include details about:

    • Performance metrics: Specific thresholds for accuracy, sensitivity, specificity, AUC, F1-score, etc.
    • Study design: Prospective/retrospective, sample size, data source.
    • Ground truth establishment: How the "truth" was determined for the test cases (e.g., expert consensus, pathology, clinical outcomes).
    • Expert qualifications and adjudication: Details about the radiologists/clinicians involved.
    • Human-in-the-loop studies (MRMC): If applicable, how AI assistance improved human performance.
    • Stand-alone performance: Algorithm-only results.
    • Training data details: Size and ground truth establishment for the training set.
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