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

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

The CO2 Laser Therapy Machine is a carbon dioxide laser used in medical and aesthetic industry for treatment of such skin conditions as fine and coarse wrinkles, scars of various origin, uneven pigmentation and dilated pores. Due to the CO2 laser's high absorption of water, its high-energy beam of laser light interacts with the skin's surface causing the upper layer to peel off and use photothermolysis to stimulate deep cell regeneration and then achieve the target of skin improvement.

The proposed device is mainly used for human tissue vaporization, carbonization, coagulation and exposure to achieve the purpose of treatment.

The CO2 Laser Therapy Machine includes three models in this submission, FG 900, FG 900-B and FG 900-C, all three models have same principle, software, operation etc., only differences are appearance.

The proposed device includes the following components: Surgery tip, Surgery tip Arm, Touchscreen, Emergency Switch, Key Switch, Goggles for Patient, Goggles for Doctor, Foot Switch.

The provided document is a 510(k) Summary for a CO2 Laser Therapy Machine. It describes the device, its intended use, and a comparison to a predicate device to demonstrate substantial equivalence.

Here's an analysis of the acceptance criteria and study information based on the provided text:

1. A table of acceptance criteria and the reported device performance

The document presents a comparison of the proposed device against a predicate device across various parameters. It doesn't explicitly state "acceptance criteria" for each parameter with numeric thresholds, but rather lists characteristics that are considered "Substantially Equivalent (SE)" if they match or are comparable to the predicate. The performance is reported as the proposed device's specifications.

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

The document states: "No clinical study is included in this submission." The evaluation is based on non-clinical tests and comparisons to a predicate device. Therefore, there is no "test set" in the sense of patient data, and no data provenance information for such a set.

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 with patient data was used to establish ground truth.

4. Adjudication method for the test set

Not applicable, as no clinical study or test set with patient data was used.

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. The device is a CO2 Laser Therapy Machine, not an AI-assisted diagnostic device.

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

Not applicable. The device is a medical instrument, not an algorithm. Performance was evaluated through non-clinical testing of the physical device. The device itself is "standalone" in that it performs its intended function without requiring human intervention in that specific function, but it is operated by a human.

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

For the non-clinical tests, the "ground truth" was established by compliance with international standards (e.g., IEC 60601-1, IEC 60601-2-22, IEC 60825-1, ISO 10993-5, ISO 10993-10) and verification of design specifications such as Spot Size Accuracy and Energy Output Accuracy, and Software Validation & Verification. These standards and specifications serve as the "ground truth" for the device's technical and safety performance.

8. The sample size for the training set

Not applicable, as this is a physical medical device, not a machine learning algorithm.

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

Not applicable, as this is a physical medical device, not a machine learning algorithm.

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