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510(k) Data Aggregation
(192 days)
Fractional CO2 Laser Therapy System (FG900-S); Fractional CO2 Laser Therapy System (FG900-S2)
Fractional CO2 Laser Therapy System is used for body soft tissue ablation, vaporization, excision and coagulation in dermatology plastic surgery and general surgery.
Fractional CO2 Laser Therapy System consists of a main unit, a light guide arm (including a treatment head), a foot switch, and protective goggles. The fractional CO2 laser penetrates directly into the dermis utilizing the thermal effect of laser, instantly vaporizes the tissue in the lesion area. Parameters such as the laser energy density required for the treatment are set by the user appropriately. The Fractional CO2 Laser Machine has two operational modes, fractional mode and normal mode.
Based on the provided text, the device in question is a "Fractional CO2 Laser Therapy System (FG900-S); Fractional CO2 Laser Therapy System (FG900-S2)". The document does not contain information about acceptance criteria or a study proving the device meets those criteria in the context of AI/algorithm performance.
Instead, the document is a 510(k) premarket notification for a medical device (a laser system) and focuses on demonstrating its substantial equivalence to a legally marketed predicate device through non-clinical testing. It explicitly states:
"No clinical study is included in this submission."
Therefore, I cannot provide the requested information regarding acceptance criteria, device performance, sample sizes, ground truth establishment, or any studies related to AI/algorithm performance. The document only discusses the physical and electrical characteristics of the laser device and its general safety and effectiveness in comparison to a predicate device, as required for a 510(k) submission.
The questions you've asked (sample size for test/training sets, data provenance, expert consensus, MRMC studies, standalone algorithm performance) are highly relevant to the evaluation of AI/ML-based medical devices. This document, however, describes a traditional medical device submission for a laser system which does not appear to involve AI/ML components for which such performance criteria would be established and studied.
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