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For Model J6-126, J6-136:
The Dental Handpiece is intended for removing carious material, excess filling material, cavity and crown preparation, finishing tooth preparations and restorations, root canal preparations and polishing teeth.
For Model SH11W2, SH11W3, W401LW, W15LW, W142LW, W11L:
The Dental Handpiece is intended for cutting and grinding teeth, cavity preparations, tooth and crown preparations, finishing and trimming teeth and filling materials and removal of crowns and filling materials.

The Dental Handpiece is mainly composed of a machine head, handle, transmission shaft, and cartridge, and is designed to be attached to the drive via standard coupling which complies with ISO 3964 and hose connector which complies with ISO 9168. The head clamp accepts an instrument complying with ISO 1797-1. The handpieces are intended to be powered by air-powered or electric-powered, and they are also intended to provide optic series. They are intended to be provided non-sterile, so they must be sterilized prior to first use and sterilized after each subsequent use using steam sterilization (moist heat sterilization).

The provided document is a 510(k) Premarket Notification for a Dental Handpiece. This type of submission is focused on demonstrating substantial equivalence to a previously cleared device, rather than proving efficacy through clinical studies or setting and meeting specific acceptance criteria for performance as would be done for a novel device or a device requiring a PMA.

Therefore, the document does not contain the information requested regarding acceptance criteria and studies that prove the device meets those criteria in the context of diagnostic or actionable performance (e.g., accuracy, sensitivity, specificity for a diagnostic AI). The "acceptance criteria" discussed in this document refer to adherence to established safety and performance standards for dental handpieces, and "study" refers to non-clinical tests verifying compliance with these standards.

Here's why the requested information isn't available in this document:

• Device Type: A "Dental Handpiece" is a physical tool used for mechanical dental procedures (cutting, grinding, polishing). It's not a diagnostic device, an AI algorithm for image analysis, or a device that generates a patient-specific "result" that would require performance metrics like sensitivity or specificity.
• Regulatory Pathway (510(k)): The 510(k) pathway demonstrates that a new device is "substantially equivalent" to a legally marketed predicate device. This typically involves comparing design, materials, technological characteristics, and intended use, and running non-clinical tests to show adherence to relevant performance and safety standards. It generally does not require large-scale clinical trials or MRMC studies that would describe the kind of acceptance criteria you've outlined.
• No Clinical Testing: The document explicitly states: "Clinical testing was not included in the submission." This immediately tells us that there will be no data on human reader improvement with AI assistance, standalone algorithm performance, or ground truth established from clinical outcomes.
• "Ground Truth" irrelevant: For a dental handpiece, the concept of "ground truth" (e.g., for a diagnosis) is not applicable. Its "performance" is measured by its physical characteristics, safety, and ability to perform its mechanical function according to engineering standards.
• No AI component: There is no mention of an AI component in this device.

Based on the available document, I cannot fulfill your request as it pertains to a diagnostic/AI device. The document describes a traditional medical device (dental handpiece) and its regulatory clearance via a 510(k) pathway, which focuses on substantial equivalence and compliance with engineering and safety standards, not clinical performance metrics relevant to AI or diagnostic accuracy.

However, I can extract information related to the standards and non-clinical tests that were performed to demonstrate the device's adherence to established safety and performance requirements, which are the "acceptance criteria" in this context.

Summary of Acceptance Criteria and Device (Non-Clinical) Performance:

Here's why the other points of your request cannot be answered from this document:

1. Sample size used for the test set and data provenance: Not applicable in the context of diagnostic/AI performance. The "tests" are engineering and safety verification tests on physical units of the device. The provenance of the device under test would be "Guangdong JINME Medical Technology Co., Ltd., China."
2. Number of experts used to establish the ground truth... and qualifications: Not applicable. There is no diagnostic "ground truth" to establish for a dental handpiece.
3. Adjudication method: Not applicable.
4. Multi-Reader Multi-Case (MRMC) comparative effectiveness study: Explicitly stated "Clinical testing was not included in the submission." Therefore, no MRMC study, no human reader improvement data.
5. Standalone (i.e., algorithm only without human-in-the-loop) performance: Not applicable, as there is no algorithm component.
6. Type of ground truth used: Not applicable.
7. Sample size for the training set: Not applicable, as there is no AI or machine learning component that requires a training set.
8. How the ground truth for the training set was established: Not applicable, as there is no training set.

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The Dental Unit is intended to supply power to and serve as a base for dental devices, and accessories. It is intended for use in the dental clinic /office environment and used by trained dentists and/or dental technicians and assistants. This product is attached with a dental chair.

The Dental Unit(model: Mare) is a dental treatment unit tested in accordance with IEC 80601-2-60. This product is used in dentistry only and may only be used by trained medical personnel and trained professional in the field of general dentistry. Dental Unit (model: Mare) consists of dental chair, arm dentist unit, assistant's unit, dental light, cuspidor, water unit, and multi-function foot control. It mainly relies on electricity, compressed air, water to achieve all functions. Various ancillary dental devices can be connected to the Dental Unit (model: Mare) which are attached by means of industry standard ISO connections. The ancillary dental devices include pneumatic handpieces, 3-way syringe, strong suction and weak suction vacuum instruments. The ancillary dental devices include 3-way syringe, strong suction and weak suction vacuum instruments are 510k clarence in the K142206. Based on Safety does not manufacture pneumatic handpieces, the pneumatic handpieces shall be purchased by the enduser. The recommended pneumatic handpieces are 510(k) clearance K170229 and K170236, which are held by GUANGDONG JINME MEDICAL TECHNOLOGY CO., LTD. None of the Dental Unit (model: Mare), parts or accessories are provided sterile.

This document is a 510(k) premarket notification for a dental unit, indicating it's primarily a regulatory submission for device clearance. It does not contain the detailed acceptance criteria and study results typically found in reports specifically designed to demonstrate device performance against such criteria for AI/ML devices.

The document discusses the substantial equivalence of the "Dental Unit: model Mare" to a predicate device (K142206). The "acceptance criteria" here refers to the compliance with recognized consensus standards for medical devices and the demonstration of safety and effectiveness through non-clinical testing.

Here's an attempt to extract the requested information based on the provided text, with the understanding that it's a regulatory submission and not a performance study report:

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

The "acceptance criteria" for a medical device in a 510(k) submission are typically compliance with recognized standards. The "reported device performance" is the statement that the device meets these standards.

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

This document describes non-clinical testing against standards for a physical medical device (dental unit), not an AI/ML diagnostic or prognostic tool. Therefore, the concept of a "test set" in the context of data used for algorithm evaluation (as implied by the question) is not applicable here. The testing involves physical testing of the device itself to conform to engineering and safety standards. No information on data provenance (country, retrospective/prospective) is provided as it's not relevant 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 (e.g. radiologist with 10 years of experience)

Not applicable. This is not an AI/ML device requiring expert-established ground truth for a test set. The "ground truth" is established by the specifications of the recognized consensus standards.

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

Not applicable. This is not an AI/ML device requiring adjudication of a test set.

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. This document explicitly states in Section 8: "There was no clinical testing performed." This is for a dental unit, not an AI-assisted diagnostic tool.

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

Not applicable. This is a physical dental unit, not an algorithm.

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

For this device, the "ground truth" is defined by the technical specifications and requirements outlined in the referenced international and national consensus standards (e.g., IEC 60601-1 for electrical safety, ISO 7494-1 for dental unit general requirements). Compliance with these standards is the ground truth for performance.

8. The sample size for the training set

Not applicable. This is a physical medical device, not an AI/ML model that requires a training set.

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

Not applicable. This is a physical medical device, not an AI/ML model.

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