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510(k) Data Aggregation

    K Number
    K023236
    Manufacturer
    Date Cleared
    2002-11-12

    (46 days)

    Product Code
    Regulation Number
    878.4460
    Reference & Predicate Devices
    Why did this record match?
    Device Name :

    SENSICARE -C SYNTHETIC POLYISOPRENE POWDER-FREE SURGICAL GLOVES

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

    A surgeon glove is a disposable device intended for medical purposes that is worn on the surgeon's hand to prevent contamination between patient and surgeon.

    Device Description

    The device in this 510(k) submission is the SensiCare -C Synthetic Polyisoprene Powder-free Surgical Glove (Classification number 79KGO). The SensiCare C Synthetic Polyisoprene Powder-free Surgical Glove is a sterile, synthetic rubber latex surgical glove. These gloves are intended to be used as a barrier by providing protection for surgical personnel and patients against microbial migration and to protect a surgical wound from contamination.

    AI/ML Overview

    The provided text describes the SensiCare-C Synthetic Polyisoprene Powder-Free Surgical Gloves and their regulatory clearance, but it does not contain information about a study involving an AI/Machine Learning device or its performance criteria, ground truth, or expert review process.

    The document is a 510(k) summary for a medical glove, focusing on its substantial equivalence to a predicate device and its compliance with relevant ASTM standards for physical properties, sterility, and freedom from holes.

    Therefore, I cannot provide the requested information regarding acceptance criteria and studies for an AI device. The input does not contain any of the following:

    • A table of acceptance criteria and reported device performance for an AI/ML system.
    • Sample sizes for test sets, data provenance, or details about training sets for an AI/ML system.
    • Information on experts used to establish ground truth or adjudication methods for an AI/ML system.
    • Details about Multi-Reader Multi-Case (MRMC) studies or standalone performance of an AI/ML system.
    • The type of ground truth used for an AI/ML system.
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