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510(k) Data Aggregation

    K Number
    K142097
    Manufacturer
    Date Cleared
    2014-08-29

    (28 days)

    Product Code
    Regulation Number
    880.5440
    Reference & Predicate Devices
    Why did this record match?
    Device Name :

    SELEC-3 I.V.ADMINISTRATION SET

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

    The SELEC-3 I.V. Administration Set is used to provide a pathway to deliver fluid into the vascular system. This product is targeted for use by nurses and paramedics in pre-hospital, emergency room and field settings.

    Device Description

    The Biomedix SELEC-3 I.V. Administration Set is a single- use, sterile device used for the administration of solutions and fully soluble drugs into the vascular system of a patient.

    AI/ML Overview

    The provided document is a 510(k) summary for the Biomedix SELEC-3 I.V. Administration Set. It describes a medical device, its intended use, and confirms that it met acceptance criteria. However, it does not describe a study involving an AI/Machine Learning device or its performance.

    Therefore, I cannot answer your request to describe the acceptance criteria and study proving an AI device's performance based on this document. The document pertains to a traditional medical device (an I.V. administration set) and its testing for safety and effectiveness, not an AI system.

    The "Testing Summary" section of the document states:
    "The SELEC-3 I.V. Administration Set has met Biomedix testing and acceptance criteria related to flow rate verification, leakage, microbial ingress, and pull force testing."

    And the "Conclusion" states:
    "The SELEC-3 I.V. Administration Set met all established acceptance criteria for design verification testing. Testing demonstrated that the device is safe and effective when used as intended."

    This indicates that internal testing was conducted to verify the design and safety of the device against predefined criteria for physical characteristics. However, these are not the types of performance metrics or study designs relevant to an AI/ML device in the context of your original query (e.g., sample sizes for test/training sets, ground truth, expert adjudication, MRMC studies, standalone performance).

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