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510(k) Data Aggregation

    K Number
    K092761
    Manufacturer
    Date Cleared
    2009-11-24

    (76 days)

    Product Code
    Regulation Number
    878.4400
    Reference & Predicate Devices
    N/A
    Why did this record match?
    Device Name :

    PROPLATE, MODELS 9641C, 9641F, P9641C, P9641F, 9642C, 9642F AND P9642C

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

    The PROPLATE is a disposable, single-use, neutral electrode, which provides a return path for high frequency electrical current to the ESU device.

    Device Description

    PROPLATE Electrosurgical Grounding Plate

    AI/ML Overview

    The provided document is a 510(k) cleared by the FDA for the 'PROPLATE Electrosurgical Grounding Plate'. This document primarily focuses on regulatory approval based on substantial equivalence to a predicate device. It certifies that the device can be legally marketed and outlines regulatory compliance requirements.

    However, the document does not contain any information regarding acceptance criteria or a study proving the device meets those criteria, as typically seen with performance data for AI/ML-enabled devices.

    Therefore, I cannot provide the requested information, including:

    1. A table of acceptance criteria and reported device performance.
    2. Sample size used for the test set or data provenance.
    3. Number of experts used to establish ground truth or their qualifications.
    4. Adjudication method for the test set.
    5. Information on a multi-reader multi-case (MRMC) comparative effectiveness study or human reader improvement with AI.
    6. Information on a standalone algorithm performance study.
    7. The type of ground truth used.
    8. Sample size for the training set.
    9. How the ground truth for the training set was established.

    This is because the device, an electrosurgical grounding plate, is a hardware medical device and not an AI/ML-enabled device. The concepts of "acceptance criteria" and "studies" as described in your prompt (e.g., ground truth, experts, training/test sets, MRMC studies) are typically relevant for the evaluation of AI/ML software as a medical device, diagnostic imaging tools, or other devices where performance is measured against a diagnostic or predictive outcome.

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