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Resor-Pin is used in oral, dental and maxillofacial surgery for the fixation of resorbable and non-resorbable membranes in augmentation and guided bone regeneration.

Resor-Pin Resorbable Membrane Pin

This is a 510(k) premarket notification for a medical device (Resor-Pin Resorbable Membrane Pin) from 1998. This type of document establishes substantial equivalence to a predicate device, rather than proving the device meets specific acceptance criteria through clinical studies. Therefore, much of the requested information regarding detailed study design, ground truth establishment, and sample sizes is not applicable or typically found in this kind of regulatory submission.

However, I can extract the following information that is present or can be inferred:

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

Since this is a 510(k) summary, specific numerical acceptance criteria and performance data from studies are not typically provided in this format. The "performance" being evaluated here is the substantial equivalence to a predicate device, meaning it performs similarly and has similar indications for use and safety profiles.

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

This information is not provided in the document. 510(k) submissions typically reference existing data or general scientific principles rather than detailing new large-scale clinical trials for substantial equivalence.

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 information is not applicable as there is no mention of a "test set" and "ground truth" establishment in the context of an AI device. This document pertains to a physical medical device.

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

This information is not applicable for the same reasons above.

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 information is not applicable as this document is for a physical medical device, not an AI-assisted diagnostic tool.

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

This information is not applicable as this document is for a physical medical device, not an algorithm.

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

This information is not applicable as there is no specific "ground truth" mentioned in the context of an AI device. The ground truth for a physical device like this would be its proven safety and effectiveness over time and through predicate device history.

8. The sample size for the training set

This information is not applicable as this document is for a physical medical device, not an AI model requiring a training set.

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

This information is not applicable as this document is for a physical medical device, not an AI model.

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