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For root canal cleaning. The instrument must only be used in hospital environments, clinics or dental offices, by qualified practitioners.

The Endo Ultrasonic Activator is mainly used for root canal cleaning.It mainly contain handpiece, sleeve, wrench, adapter and tip. The ultrasonic frequency generated by the CPU is driven by the drive circuit to drive the piezoelectric ceramic transducer, using the reverse piezoelectric effect to produce the ultrasonic vibration, motivating the working tip to produce the resonance, and using the cavitation and sound flow effect generated by the ultrasonic vibration to wash the root canal swing.

The provided text describes the regulatory clearance of a medical device, the "Endo Ultrasonic Activator," and its substantial equivalence to a predicate device. It contains a comparison table of characteristics and analysis of differences, but it does not describe specific acceptance criteria and a study proving the device meets those criteria in the typical format one would expect for an AI algorithm's performance.

This document is a 510(k) summary for a physical medical device (an ultrasonic activator for root canal cleaning), not an AI/ML powered device. Therefore, the requested information components related to AI/ML device performance (like sample sizes for test/training sets, data provenance, expert ground truth, MRMC studies, standalone performance, etc.) are not applicable and are not present in the provided text.

The "Non-Clinical Test Conclusion" and "Substantially Equivalent (SE) Comparison" sections describe how the device meets various safety and performance standards relevant to non-AI medical devices.

Here's an attempt to extract relevant information while acknowledging the non-AI nature of the document:

1. Table of Acceptance Criteria and Reported Device Performance

For a physical medical device, "acceptance criteria" are typically compliance with recognized standards. The "reported device performance" is demonstrated through testing against these standards and comparison to a predicate device.

2. Sample size used for the test set and the data provenance
Not Applicable (N/A). This document refers to the testing of a physical medical device, not an AI/ML algorithm that would typically have a "test set" of data. The testing involved compliance with various engineering and safety standards, likely through bench testing and material evaluations.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts
N/A. No ground truth establishment by experts for a test set is described as this is not an AI/ML device.

4. Adjudication method (e.g., 2+1, 3+1, none) for the test set
N/A. No test set or corresponding adjudication method is described.

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/ML device, so no MRMC study or AI assistance effect size is discussed.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
N/A. This is not an AI/ML device.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.)
N/A. No ground truth is described in the context of an AI/ML algorithm. The "truth" for this device's performance is its compliance with engineering, safety, and biocompatibility standards, and demonstrating the same fundamental operating principle as a legally marketed predicate device.

8. The sample size for the training set
N/A. This is not an AI/ML device.

9. How the ground truth for the training set was established
N/A. This is not an AI/ML device.

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