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The Medical Diode Laser (Model: L2) is indicated for:
-Incision, excision, ablation, vaporization, hemostasis and/or coagulation of soft tissue
-Endovascular coagulation and endovenous occlusion of the greatest saphenous vein in patients with superficial vein reflux

The Medical Diode Laser use a wavelength 1470nm Galium Aluminum Arsenide (GaAlAs) diode laser as the beam source. The laser utilizes a red (650nm) aiming beam diode to indicate the area to be irradiated by the laser beam. The Medical Diode Laser (model: L2) is a compact diode laser with a LCD touchscreen for user control. The device is composed of main unit, foot switch, power cord and protective goggles. The fiber delivery system is not included in this device. The device accepts a fiber with single core of 400um and 600um in diameter and with SMA905 connectors.

The provided text is an FDA 510(k) clearance letter and summary for a Medical Diode Laser. It outlines the characteristics of the device and its comparison to a predicate device to establish substantial equivalence.

Crucially, this document does not describe a study involving an AI/Machine Learning device or a diagnostic device. The device described is a Medical Diode Laser, a surgical instrument. The performance data presented refers to bench testing for electrical safety, functional performance, and compliance with laser safety standards, not to the assessment of an algorithm's performance against ground truth in a clinical setting.

Therefore, many of the requested criteria related to AI/ML device performance (like sample size for test/training sets, expert consensus, MRMC studies, standalone performance, ground truth establishment, etc.) are not applicable to this type of device and are not found in the provided text.

Here's how the information that is applicable can be extracted:

Acceptance Criteria and Device Performance (as far as applicable to a surgical laser):

Here's an analysis of the requested information based only on the provided text:

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

   • See table above. The "acceptance criteria" for this device are primarily compliance with international safety and performance standards for medical electrical equipment and lasers, and demonstrating comparable performance characteristics to the predicate device.

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

   • N/A. This information pertains to studies of diagnostic algorithms or clinical trials. For a surgical laser, performance is assessed through bench testing and compliance with engineering standards. No clinical 'test set' in the diagnostic sense is mentioned. The data provenance is related to the testing done by "Pioon" (Wuhan Pioon Technology Co., Ltd.) in China.

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):

   • N/A. Ground truth for diagnostic accuracy is not relevant for this device. Its "performance" is based on physical output (e.g., laser power, wavelength) and safety compliance.

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

   • N/A. Not relevant for a surgical laser's technical performance assessment.

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 a surgical laser, not an AI-assisted diagnostic tool. No human readers or MRMC studies were conducted or are applicable.

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

   • N/A. Not an AI algorithm. Its performance is inherent to its physical operation.

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

   • N/A. The "ground truth" for a laser would be its measured physical properties (e.g., power output, wavelength), electrical safety parameters, and software functionality, validated against engineering standards.

8. The sample size for the training set:

   • N/A. No training set is involved as this is not a machine learning device.

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

   • N/A. No training set is involved.

In summary, the provided document describes the FDA clearance process for a common medical device (a surgical laser) by demonstrating substantial equivalence to a legally marketed predicate device, primarily through non-clinical bench testing and compliance with relevant safety and performance standards. It does not provide information relevant to the assessment of an AI/ML diagnostic algorithm.

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