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Incision, excision, ablation, vaporization of soft tissue for general dermatology (1064 nm) Removal or lightening of unwanted hair with or without adjuvant preparation (1064nm) Tattoo Removal: Dark ink (blue and black) (1064 nm) Tattoo Removal: light ink (red, sky blue, green) (532 nm) port wine birthmarks (532 nm) telangiectasias (532 nm) spider angioma (532 nm) cherry angioma (532 nm) spider nevi (532 nm) cafe-au-lait birthmarks (532 nm) solar lentiginos, senile lentiginos, becker's nevi, freckles, nevus spilus (532 mm) nevus of ota (1064 nm)

The Helios III laser system is based on the Nd:YAG (1064 nm) and frequency doubled KTP Nd:YAG (532 nm) laser technology. Three basic elements of operations are as follows: 1) A Nd:YAG crystal is used as a gain medium which produces a laser beam. 2) A resonator then amplifies the beam. 3) A lamp that contains Xe gas is used, as a pumping light source. The lamp requires a high-pressure power source device for operation. When the electric energy generated from the high-pressure power source is induced into the electrode of the lamp, it converts into light energy. This converted light energy pumps the Nd–YAG crystal – a gain medium – and the light exhausted from the crystal is amplified into a specific wavelength light. As it passes between the resonant gases, laser beam radiates to an output unit. The regulation of laser output and repetition rate can be set by the user via GUI (Graphic User Interface) and controlled by microprocessor, which interfaces with the power supply.

The provided text is a 510(k) summary for the Helios III Q-Switched Nd:YAG Laser System. It is an FDA submission seeking substantial equivalence to existing predicate devices, not a study proving the device meets specific acceptance criteria through clinical or AI-driven performance metrics.

The document primarily focuses on bench testing and comparison of technical specifications and intended uses with predicate devices to demonstrate substantial equivalence, rather than providing the kind of performance data you are asking for regarding AI/human reader studies.

Therefore, many of the requested items (e.g., acceptance criteria for AI performance, sample size for test/training sets, expert ground truth establishment, MRMC studies, standalone AI performance) are not applicable (N/A) because this is not a submission for an AI/ML medical device or a clinical outcome study in the traditional sense you have described.

Here's a breakdown of the information that is available in the provided text:

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

The document doesn't provide explicit "acceptance criteria" in the format of pass/fail thresholds for clinical or AI performance. Instead, it presents a comparison of the Helios III's technical specifications and intended uses against two predicate devices recognized as legally marketed. The "performance" is demonstrated by showing that these specifications are comparable to or within acceptable ranges of the predicates.

Table 1: Approved Indication of Uses for Helios III Predicate Devices (Comparative)

Table 2: Performance Specification Comparison with Predicate Devices (Comparative)

Regarding the Study:

The document states:

• Performance Data: "Non-clinical testing of Helios III included visual and mechanical inspection, electrical and mechanical safety testing, functional performance testing, etc., in bench. Some of these tests include visual inspection, earthbond testing, software testing, transit testing, leakage current testing and measurements. Test reports have been submitted."
• This refers to bench testing for safety and functional performance as a laser device, not a comparative clinical study or AI performance evaluation.

Specific Answers to Your Questions (based on the provided text):

2. Sample sizes used for the test set and the data provenance: N/A. This document describes non-clinical bench testing of a laser device, not performance on a test set of medical images or patient data. Data provenance (country, retrospective/prospective) is also N/A for this type of submission.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: N/A. Ground truth establishment by experts is not described for this type of device submission.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set: N/A. No adjudication process for a test set is mentioned.
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: N/A. This is not an AI-assisted device.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: N/A. This is not an AI algorithm.
7. The type of ground truth used (expert concensus, pathology, outcomes data, etc): N/A. For the bench testing, "ground truth" would be the engineering specifications and safety standards met by the device.
8. The sample size for the training set: N/A. This device does not involve a training set as it is not an AI/ML product.
9. How the ground truth for the training set was established: N/A. Not an AI/ML product.

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