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510(k) Data Aggregation

    K Number
    K013692
    Device Name
    TRAPSYSTEM SET
    Date Cleared
    2002-02-05

    (90 days)

    Product Code
    Regulation Number
    876.1075
    Reference & Predicate Devices
    Why did this record match?
    Device Name :

    TRAPSYSTEM SET

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

    This biopsy instrument is used for drawing of osteomedullary substance and or for explantation of bone marrow.

    Device Description

    A disposable single use Biopsy Needle. The product consist of a 304 stainless steel cannula and 302 stainless steel stylet. The cannula is inserted molded into an ABS hub that provide a grip for manipulation of the Needle. Inside of the cannula is a stylet made by 302 stainless steel, inserted molded into an ABS hub. An additional patented stylet is provided to be used for trapping the sample in the cannula. An extracting 302 stainless steel wire with safety grip. The protective cover of cannula is made of polypropilene.

    AI/ML Overview

    The provided document is a 510(k) summary for a medical device (TrapSystem® Set Bone Marrow Biopsy Needle) and does not contain information on acceptance criteria, device performance studies, or details relevant to artificial intelligence/machine learning (AI/ML) device performance.

    Therefore, I cannot extract the requested information regarding:

    • A table of acceptance criteria and reported device performance.
    • Sample size for the test set and data provenance.
    • Number and qualifications of experts for ground truth.
    • Adjudication method for the test set.
    • Multi-Reader Multi-Case (MRMC) comparative effectiveness study results.
    • Standalone (algorithm only) performance.
    • Type of ground truth used.
    • Sample size for the training set.
    • How ground truth for the training set was established.

    This document is for a conventional medical device (a biopsy needle) seeking substantial equivalence and does not involve AI/ML components or associated performance studies as typically found in submissions for AI/ML-powered devices.

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