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Star+ VPS Scannable Impression Material is an addition-cured vinyl polysiloxane dental impression material that is used for all crown and bridge, edentulous, and implant techniques. The impression material can also be scanned by dental impression scanners

Star+ VPS Scannable Impression Material is an addition-cured vinyl polysiloxane dental impression material.

I am sorry, but the provided text does not contain the information required to describe the acceptance criteria and study proving device performance. The document is an FDA 510(k) clearance letter for a dental impression material, and it primarily focuses on the regulatory approval process and indications for use, rather than detailed performance study results.

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Prestige is a dental composite restorative material designed to be used in all classes of cavities

Prestige™ is a light-cured, Nanohybrid dental restorative material intended for use for the restoration in all classes of cavities

The provided document is a 510(k) premarket notification for a dental composite restorative material named "Prestige." It does not describe an AI/ML-driven device or study. Therefore, most of the requested information regarding acceptance criteria, study design, sample sizes, expert qualifications, and ground truth establishment for such a device is not applicable to this document.

The document discusses the "Prestige" dental composite restorative material and its substantial equivalence to a predicate device (Herculite XR & XRV). It focuses on non-clinical performance testing for material properties.

However, I can extract the relevant information from the document that pertains to the non-clinical performance testing conducted for the "Prestige" device to demonstrate substantial equivalence.

Here's the information that can be extracted, interpreted in the context of material performance rather than AI/ML algorithms:

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

The document states that the substantial equivalence is supported by "Physical and Mechanical Properties performance testing." While explicit acceptance criteria values are not given in this summary, the reported performance is that the Prestige™ device "has the same performance and technological characteristics" as the predicate device, and that bench testing indicates its suitability for the intended purpose. The overall acceptance criterion for the 510(k) submission is to demonstrate substantial equivalence to the predicate device.

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

• Sample Size: Not specified in the provided summary. The non-clinical testing refers to "in-house testing" and "side-by-side comparisons" but does not give specific numbers of samples or units tested for each property (e.g., number of specimens for flexural strength).
• Data Provenance: The testing was conducted as "in-house testing" by Danville Materials LLC, located in San Ramon, California, USA. The data would be prospective in relation to the submission, as it was generated specifically to support the 510(k) application.

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)

This is not applicable as the document describes a dental restorative material, not an AI/ML device that requires expert-established ground truth for image interpretation or diagnosis. The "ground truth" for this device would be the objective measurements of its material properties.

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

This is not applicable as the document describes a dental restorative material, not an AI/ML device requiring adjudication of human interpretations.

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

This is not applicable as the document describes a dental restorative material, not an AI/ML device.

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

This is not applicable as the document describes a dental restorative material, not an AI/ML device. The "standalone" performance here would refer to the intrinsic material properties measured in a lab, which are described as being tested.

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

The "ground truth" for this device's performance would be the objective, empirically measured physical and mechanical properties of the material itself (e.g., actual flexural strength values, depth of cure measurements, radiopacity readings, etc.) using established testing standards and methodologies for dental materials.

8. The sample size for the training set

This is not applicable as the document describes a dental restorative material, not an AI/ML device that requires a training set.

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

This is not applicable as the document describes a dental restorative material, not an AI/ML device that requires a training set and associated ground truth.

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DMRC Bulk Fill is a dual-cure (auto-cure) with light-cure acceleration) polymer-based dental restoratives that when applied to dental surfaces pretreated with suitable primers or adhesives are use as the first incrual with posterior composites, for core build-ups; and for luting posts, crowns, veneers sead any application there light transmission may be inadequate

DMRC Bulk Fill is a dual-cure (auto-cure) with light-cure acceleration) polymer-based dental restoratives

This document is a 510(k) premarket notification letter for a dental restorative material called "DMRC Bulk Fill." It focuses on the regulatory approval process and does not contain the kind of detailed clinical study information (acceptance criteria, device performance tables, sample sizes, expert qualifications, etc.) that you've requested regarding device performance and its proof.

Therefore, I cannot extract the requested information from the provided text.

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This device is a one step no-mix adhesive for direct bonding of orthodontic bracket to tooth structure

The DMRC Self-Cure Bracket Adhesive One Step and Primer is a resin based adhesive designed for direct bonding of orthodontic brackets with no-mix step.

The document describes the DMRC Self-Cure Bracket Adhesive One Step and Primer and its substantial equivalence to a predicate device based on non-clinical testing.

Here's the information requested:

1. Table of Acceptance Criteria and Reported Device Performance:

The document does not explicitly state "acceptance criteria" in a quantitative sense with pass/fail thresholds. Instead, it presents the results of bench testing for the DMRC Self-Cure Bracket Adhesive One Step and Primer alongside the predicate device's performance to demonstrate "equivalence." The implied acceptance criterion is that the new device's performance is comparable to or better than the predicate device.

2. Sample Size Used for the Test Set and Data Provenance:

The document does not specify the exact sample sizes (e.g., number of specimens tested) for the Vicker's Hardness, Shear Bond Strength, or Self-Cure Set Time tests. It also does not explicitly mention the country of origin of the data or whether the data was retrospective or prospective. These were non-clinical bench tests, not human studies.

3. Number of Experts Used to Establish the Ground Truth for the Test Set and Their Qualifications:

Not applicable. The "test set" here refers to non-clinical bench tests on materials, not a set of clinical cases requiring expert interpretation.

4. Adjudication Method for the Test Set:

Not applicable for non-clinical bench tests. The results are quantitative measurements.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done:

No, an MRMC comparative effectiveness study was not done. This product is a dental adhesive, and the evaluation was based on non-clinical material properties.

6. If a Standalone (Algorithm Only Without Human-in-the-Loop Performance) Was Done:

Not applicable. This is not an AI/algorithm-based device.

7. The Type of Ground Truth Used:

For the non-clinical tests, the "ground truth" is the quantitative measurement obtained through standardized laboratory testing procedures for properties like Vicker's Hardness, Shear Bond Strength, and Self-Cure Set Time.

8. The Sample Size for the Training Set:

Not applicable. This is not an AI/machine learning device that requires a training set.

9. How the Ground Truth for the Training Set Was Established:

Not applicable. This is not an AI/machine learning device.

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DMRC Dual Cure Orthodontic Band Cement is a dual-cure adhesive intended for use as an orthodontic band cement for bonding of orthodontic bands to enamel

DMRC Dual Cure Orthodontic Band Cement is a resin based material containing a dual-cure adhesive for cementation of orthodontic bands. The DMRC Dual Cure Orthodontic Band Cement is a polymer based filling and restorative material; it contains a base and catalyst for dual curing process as orthodontic band cement.

The provided text is related to a 510(k) premarket notification for a dental adhesive device, DMRC Dual Cure Orthodontic Band Cement. This type of document is for regulatory clearance of a medical device and thus does not include information on acceptance criteria for software, detailed clinical study designs, or AI performance metrics.

Therefore, I cannot provide the requested information for the following reasons:

1. The document is not about AI software or a device that uses AI. It concerns a dental adhesive for orthodontic bands, which is a physical material, not a digital diagnostic or treatment support tool.
2. The document does not detail acceptance criteria for software performance. The "acceptance criteria" mentioned in the context of the device are for its physical properties and biocompatibility, not for accuracy, sensitivity, or specificity of an algorithm.
3. No study is mentioned that proves the device meets AI-specific acceptance criteria. The "studies" mentioned are non-clinical bench tests (Vickers Hardness, Ultradent Bracket Shear Bond Strength, Work and Set times, ISO 10993 cytotoxicity) to demonstrate performance comparable to a predicate device. These are standard for material-based medical devices.
4. There is no mention of sample sizes for test sets, data provenance, ground truth experts, adjudication methods, MRMC studies, standalone algorithm performance, or training set details, as these are all relevant to AI/software performance evaluation, which is not applicable to this device submission.

In summary, the provided text does not contain any information relevant to the acceptance criteria or study design for an AI-powered medical device.

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