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510(k) Data Aggregation

    K Number
    K092285
    Date Cleared
    2009-08-28

    (30 days)

    Product Code
    Regulation Number
    892.5050
    Reference & Predicate Devices
    N/A
    Predicate For
    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    To provide dosimetry or to detect the dose delivered to a patient during therapeutic radiation procedures. The system is intended for the verification of the output of radiation producing devices.

    Device Description

    Portable Dosimeter

    AI/ML Overview

    This document is a 510(k) clearance letter from the FDA for a device called "Portable Dosimeter". This letter does not contain the detailed technical information such as acceptance criteria, study details, and performance metrics that would be present in a 510(k) summary or the original submission itself.

    Therefore,Based on the provided text, I cannot extract the requested information. The document is an FDA clearance letter and does not contain details about:

    1. Acceptance criteria and reported device performance: This letter states that the device is "substantially equivalent" to a predicate device, but it does not provide specific performance metrics or acceptance criteria used in the substantial equivalent determination.
    2. Sample size used for the test set and data provenance: No study details are included.
    3. Number of experts used to establish the ground truth for the test set and their qualifications: No study details are included.
    4. Adjudication method for the test set: No study details are included.
    5. Multi-reader multi-case (MRMC) comparative effectiveness study: No study details are included, and given the nature of a dosimeter, an MRMC study is unlikely to be relevant.
    6. Standalone performance (algorithm only without human-in-the-loop performance): This is a hardware device (dosimeter), not an AI algorithm.
    7. Type of ground truth used: No study details are included.
    8. Sample size for the training set: This is a hardware device; a "training set" in the context of an AI algorithm is not applicable.
    9. How the ground truth for the training set was established: Not applicable.
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