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510(k) Data Aggregation

    K Number
    K213484
    Manufacturer
    Date Cleared
    2022-04-20

    (173 days)

    Product Code
    Regulation Number
    878.4810
    Reference & Predicate Devices
    Predicate For
    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    The SmoothCool HR System is indicated for hair removal (permanent hair reduction).

    Device Description

    SmoothCool HR System is an Intense Pulsed Light (IPL) system used for hair removal (permanent hair reduction) in the area of dermatology. The system consists of a console containing the power unit and control electronics with control and display panel including software. Applicators/hand pieces are connected to the system in order to generate light energy for treatment. Four different hand pieces are offered with the system.

    AI/ML Overview

    The provided document is a 510(k) summary for the SmoothCool HR System, which is an Intense Pulsed Light (IPL) system for hair removal. It aims to demonstrate substantial equivalence to predicate devices, not to describe the acceptance criteria and study that proves the device meets those criteria in the way typically associated with AI/ML-based medical devices or diagnostic devices involving performance metrics like sensitivity, specificity, or AUC.

    Therefore, the specific information requested in the prompt (e.g., acceptance criteria table, sample size for test set, number of experts, adjudication method, MRMC study, standalone performance, ground truth type, training set sample size, how ground truth was established for training set) is not present in this document.

    This document focuses on regulatory equivalence for a hardware device (IPL system) based on updated components and technical characteristics rather than a software algorithm's performance against clinical endpoints or expert consensus. The "tests" mentioned are for energy output and electrical safety/EMC, which are standard for such physical devices, not performance evaluation against clinical outcomes or a ground truth as would be relevant for devices that interpret data or diagnose conditions.

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