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The CO2 Laser Machine is used for human tissue vaporization, coagulation in dermatology and plastic surgery, general surgery, gynecology, podiatry, dental and otorhinolaryngology.

The CO2 Laser Machine is used for human tissue vaporization, coagulation in dermatology and plastic surgery, general surgery, gynecology, podiatry, dental and otorhinolaryngology.

The CO2 laser machine has two modes, continuous mode and multi-pulse mode. It utilizes CO2 laser to vaporize and heat tissue.

During the treatment, the water in skin tissues absorbs laser energy and then vaporizes.

Laser parameters and other system features are controlled from the control panel on the console, which provides an interface to the system's micro-controller through a LCD touch-screen.

The provided text does not describe acceptance criteria for a medical device's performance, nor does it detail a study proving its performance against such criteria.

Instead, this document is a 510(k) summary for a CO2 Laser Machine, Model: BW-203B, seeking market clearance from the FDA. The purpose of a 510(k) submission is to demonstrate that a new medical device is substantially equivalent to a legally marketed predicate device, meaning it is as safe and effective as the predicate and does not raise different questions of safety and effectiveness.

The document focuses on comparing the proposed device to a predicate device (K200042) in terms of general characteristics, performance specifications, and safety standards.

Therefore, I cannot provide the requested information about acceptance criteria and a study proving the device meets them from the given text.

However, I can extract information related to the comparison with the predicate device and the non-clinical tests performed:

1. Table of Acceptance Criteria and Reported Device Performance:

The document doesn't present "acceptance criteria" in the traditional sense of performance metrics that the device's output is measured against. Instead, it compares the proposed device's specifications and compliance with safety standards against a predicate device. The "Remark" column indicates if the characteristic is "SAME" or "SIMILAR."

2. Sample size used for the test set and the data provenance:

The document explicitly states: "No clinical study is included in this submission." This implies there was no "test set" in the context of clinical performance evaluation. The evaluation for substantial equivalence was based on non-clinical tests (bench testing, standards compliance) and comparison to the predicate device's specifications.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:

Not applicable, as no clinical study or test set requiring expert ground truth was conducted.

4. Adjudication method for the test set:

Not applicable, as no clinical study or test set was conducted.

5. If a multi reader multi case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance:

Not applicable. This device is a CO2 Laser Machine for surgical use, not an AI-assisted diagnostic or imaging device that would typically involve human readers.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:

Not applicable. This device is hardware for surgical procedures, not an algorithm.

7. The type of ground truth used:

Not applicable. The "ground truth", in this context, is the compliance with established electrical, laser, and biocompatibility safety standards (IEC, ISO) and the functional specifications demonstrated through non-clinical testing.

8. The sample size for the training set:

Not applicable, as no AI/algorithm training was performed or reported.

9. How the ground truth for the training set was established:

Not applicable, as no AI/algorithm training was performed or reported.

Summary of what the document does provide:

The document focuses on demonstrating substantial equivalence to a predicate device (K200042) through:

• Comparison of technical specifications: Maximum power, work mode, wavelength, beam delivery, control system, cooling system, etc.
• Compliance with recognized standards: IEC 60601-1, IEC 60601-2-22, IEC 60825-1, IEC 60601-1-2, ISO 10993-5, ISO 10993-10.
• Non-clinical testing: This involved verifying that the proposed device met design specifications and complied with the listed safety standards. It also mentions "Software Validation & Verification Test."
• Conclusion: Based on the comparison and non-clinical tests, the proposed device is determined to be Substantially Equivalent (SE) to the predicate device.

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The Diode Laser Machine (Model: BM-100) 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.

The proposed device incorporates a diode laser that emits invisible infrared laser radiation centered on a wavelength of 808 nm. Main components of the device include the laser console, liquid crystal display (LCD) touchscreen control panel, and laser handpiece. The device emits pulses of the 808 nm infrared laser emissions at pulse widths, repetition frequency, and energy levels, conductive to hair removal. The device incorporates water cooling, air cooling fan, and switches/buttons to control the laser output. The device is powered via an alternating current power source.

This document is a 510(k) Premarket Notification from the FDA for a Diode Laser Machine (Model: BM-100) intended for hair removal. It is not a report on an AI/ML medical device, therefore, the requested information regarding acceptance criteria, study details, expert involvement, and ground truth establishment, which are typical for AI/ML device clearances, is not available in this document.

The document focuses on demonstrating substantial equivalence to a predicate device (K162659) based on design specifications, performance, and safety standards, rather than clinical performance with an AI model.

Here's a breakdown of what is in the document related to "acceptance criteria" and "proof":

Acceptance Criteria and Reported Device Performance (as per this document's scope)

The "acceptance criteria" for this device, in the context of a 510(k), are not about statistical performance metrics of an AI model, but rather demonstrating that the device is as safe and effective as a legally marketed predicate device.

The "reported device performance" refers to the technical specifications and compliance with relevant safety standards, which are compared to the predicate device.

Table of Acceptance Criteria (as implied by 510(k) comparison) and Reported Device Performance:

Study Information (as requested, but mostly N/A for this document)

This document describes a 510(k) submission for a physical medical device (diode laser machine), not an AI/ML-based diagnostic or treatment planning system. Therefore, most of the requested points are not applicable and are not found in the provided text.

1. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective):

   • N/A. This document details non-clinical laboratory testing for safety and performance (e.g., electrical safety, EMC, laser safety, biocompatibility) rather than a clinical trial with a test set of patient data.

2. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience):

   • N/A. Ground truth establishment using experts is not relevant to this type of device clearance which relies on engineering and physical performance testing and comparison to a predicate device.

3. Adjudication method (e.g. 2+1, 3+1, none) for the test set:

   • N/A. Adjudication methods are typically for clinical studies with human readers or AI outputs, which is not the subject of this 510(k).

4. If a multi reader multi case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance:

   • N/A. This document explicitly states: "No clinical study is included in this submission." An MRMC study is not relevant as this is not an AI-assisted device.

5. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:

   • N/A. This is a physical laser machine, not an algorithm.

6. The type of ground truth used (expert consensus, pathology, outcomes data, etc):

   • N/A. The "ground truth" for this device's clearance pertains to the objective measurements of its physical parameters (e.g., wavelength, power, safety compliance) against established engineering standards and specifications of the predicate device.

7. The sample size for the training set:

   • N/A. The concept of a "training set" applies to machine learning models, which is not applicable to this device.

8. How the ground truth for the training set was established:

   • N/A. Not applicable.

In summary, the provided FDA 510(k) document is for a conventional medical device (diode laser) and does not involve AI/ML components or associated clinical performance studies that establish "ground truth" or use test/training sets in the context of an algorithm. The "proof" for this device is its demonstrated substantial equivalence to a predicate device through engineering specifications and compliance with recognized safety and performance standards.

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