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The Intense Pulsed Light Treatment System (Model: HM-IPL-B8) are indicated for use in surgical and aesthetic applications in permanent hair removal, reduction of benign pigmented lesions and benign vascular lesions.

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 regimen.

The EROSE-YA device is an intense pulsed light system which delivers intense pulsed light at wavelengths ranging from 430mm-1200nm. Intense Pulsed Light (IPL) systems work on the principles of selective thermolysis. That is, causing thermal damage to target chromophores by using light of appropriate wavelength in pulses that exceeds the chromophores' thermal relaxation time but sparing normal skin by limiting the pulse width below the thermal relaxation time for skin.

IPL systems are different from lasers in that they deliver many wavelengths in each pulse of light instead of just one wavelength. Generally, IPL enhances penetration without using excessive energy levels and enables targeting of specific chromophores.

The provided text describes a 510(k) premarket notification for an Intense Pulsed Light Treatment System. The core of this submission is to demonstrate "Substantial Equivalence" (SE) to a previously cleared predicate device, rather than proving the device meets specific acceptance criteria in the sense of a clinical performance study for a novel AI device.

Therefore, the requested information regarding acceptance criteria, performance studies, sample sizes, expert ground truth, adjudication, MRMC studies, standalone performance, training sets, and how ground truth was established for a novel AI device cannot be extracted from this document.

This document primarily focuses on engineering and safety comparisons between the proposed device and a predicate device.

However, I can extract the information that is present, which relates to non-clinical testing and the basis for the "Substantial Equivalence" claim.

Here's what can be gathered:

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

The document doesn't present "acceptance criteria" in the typical sense for an AI model's performance on a specific task (e.g., accuracy, sensitivity, specificity). Instead, it demonstrates equivalence to a predicate device across various technical specifications and safety standards. The "acceptance criteria" are implied by the predicate device's specifications and compliance with relevant IEC and ISO standards.

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

• Sample size: Not applicable. This submission relies on technical and safety testing rather than a clinical performance study with a "test set" of patients/data in the AI sense.
• Data provenance: Not applicable for a clinical test set. Non-clinical tests were conducted to verify design specifications and compliance with standards.

3. 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):

• Not applicable. No clinical "ground truth" establishment by experts is described for this type of submission.

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

• Not applicable.

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:

• No, an MRMC study was not done. The device is not an AI diagnostic or assistance tool for human readers.

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

• Not applicable. This is a physical, light-based treatment system, not an algorithm.

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

• For the non-clinical tests, the "ground truth" is adherence to established engineering and safety standards (e.g., IEC 60601-1, ISO 10993-5). For substantial equivalence, the "ground truth" is the specifications and safety profile of the predicate device.

8. The sample size for the training set:

• Not applicable. This device is not an AI model that undergoes training.

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

• Not applicable. This device is not an AI model.

In summary: The provided document is a 510(k) submission for a non-AI medical device (Intense Pulsed Light Treatment System). It does not present a clinical study or performance data as would be required for an AI-powered diagnostic or therapeutic device. Instead, it demonstrates substantial equivalence to an existing predicate device based on identical intended use, technological characteristics, and compliance with recognized electrical safety, EMC, and biocompatibility standards through non-clinical testing. The submission explicitly states: "No clinical study is included in this submission."

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