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510(k) Data Aggregation

    K Number
    K241498
    Date Cleared
    2024-11-18

    (174 days)

    Product Code
    Regulation Number
    878.4810
    Reference & Predicate Devices
    Why did this record match?
    Device Name :

    Diode laser Treatment System (K18)

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

    The Diode laser Treatment System (Model: K18) is intended for hair removal, permanent hair reduction on all skin types (Fitzpatrick skin type I-VI), including tanned skin. Permanent hair reduction is defined as the long-term, stable reduction in the number of hairs regrowing when measured at 6, 9, and 12 months after the completion of a treatment regime.

    Device Description

    Diode laser Treatment System adopts Gold standard 808nm semi-conductor laser, based on selective photothermolysis principle, through specific wavelength, penetrate epidermis into dermis, optical energy was absorbed and translated into heat energy with restraining hair follicle tissues, and produce photothermal effect. It takes laser energy in hair follicle with rich in melanin, surrounding tissues absorb less even no energy, reach to restrained melanin of hair follicles and remove hair. The Diode laser Treatment System utilize a semiconductor diode with invisible infrared radiation as a laser source to emit 808nm wavelength laser which is absorbed by melanin. The laser power is delivered to the treatment area via laser handpiece. The emission laser is activated by a foot-switch.

    AI/ML Overview

    This document is a 510(k) Pre-Market Notification from the FDA, describing the substantial equivalence of a Diode Laser Treatment System (Model: K18) to a predicate device. It does not contain information about acceptance criteria and a study proving a device meets these criteria in the context of an Artificial Intelligence (AI) / Machine Learning (ML) enabled medical device.

    The entire document focuses on demonstrating that the proposed device, a Diode Laser Treatment System, is substantially equivalent to an existing predicate device based on non-clinical tests (electrical safety, EMC, laser safety, and biocompatibility).

    Here's why the requested information cannot be extracted from this document:

    • No AI/ML Component: The device described is a physical laser treatment system, not an AI/ML software or system. Therefore, there are no AI/ML specific acceptance criteria or studies to evaluate its performance in the way described in the request.
    • No Clinical Study: The document explicitly states: "No clinical study is included in this submission." This means there is no data from patient trials or diagnostic accuracy studies, which are typically used to establish performance for AI/ML devices.
    • Focus on Substantial Equivalence: The purpose of a 510(k) summary for a traditional medical device like this is to show that it is as safe and effective as a legally marketed predicate device. This is achieved through engineering tests and comparison of specifications, not through performance metrics against a human "ground truth" or expert consensus (as would be the case for AI/ML).

    Therefore, I cannot provide the requested information from the provided text for the following reasons:

    1. A table of acceptance criteria and the reported device performance: Not applicable. Performance is established through engineering and safety standards, not clinical accuracy metrics.
    2. Sample size used for the test set and the data provenance: Not applicable. No clinical test set.
    3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable. No clinical ground truth is established.
    4. Adjudication method: Not applicable.
    5. If a multi-reader multi-case (MRMC) comparative effectiveness study was done: Not applicable.
    6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not applicable.
    7. The type of ground truth used: Not applicable.
    8. The sample size for the training set: Not applicable.
    9. How the ground truth for the training set was established: Not applicable.
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