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Collagen Dental Membrane III is intended for use in dental surgery procedures as a material for placement in the area of dental implant, bone defect or ridge reconstruction to aid in wound healing post dental surgery.

Collagen Dental Membrane III is intended for use in oral surgical procedures as a resorbable material for placement in the area of dental implant, bone defect, or ridge augmentation to aid in wound healing.

Collagen Dental Membrane III is a white, nonfriable, conformable, resorbable, membrane matrix engineered from highly purified type I collagen derived from bovine Achilles tendon. It is flexible and conforms to the contours of the defect site. Collagen Dental Membrane III is supplied sterile, non-pyrogenic, in various sizes, and for single use only.

This submission describes a medical device, Collagen Dental Membrane III, intended for use in dental surgery procedures. It is a resorbable membrane matrix designed to aid in wound healing after dental implant, bone defect, or ridge reconstruction.

Here’s an analysis of the provided text based on your request, highlighting that this is not an AI/ML device and therefore many of your questions are not applicable:

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

2. Sample size used for the test set and the data provenance

This is not an AI/ML device. Therefore, the concepts of "test set," "sample size," and "data provenance" as they relate to AI model evaluation are not applicable here. The evaluation involved biocompatibility testing and comparison to a predicate device.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts

This is not an AI/ML device. "Ground truth" in the context of expert review for AI is not relevant. The evaluation of this device is based on standardized biocompatibility testing protocols and material characterization, not expert human interpretation of data for AI model training or validation.

4. Adjudication method for the test set

This is not an AI/ML device. "Adjudication method" as it applies to resolving discrepancies in expert labeling for AI models is not applicable. The device's safety and equivalence were determined through established regulatory testing and comparison methods.

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 an AI/ML device. Therefore, an MRMC comparative effectiveness study involving human readers with or without AI assistance was not conducted and is not relevant to this type of medical device submission.

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

This is not an AI/ML device. No algorithm or standalone performance evaluation was conducted because it is a physical medical device (collagen membrane), not a software or AI product.

7. The type of ground truth used

For this device, the "ground truth" aligns with established scientific and regulatory standards for medical devices:

• Biocompatibility: Determined by adherence to FDA Blue Book Memorandum G95-1 and ISO 10993-1 standards (e.g., cytotoxicity, sensitization, irritation tests). The "ground truth" is that the device, when subjected to these tests, does not elicit unacceptable biological responses.
• Substantial Equivalence: Determined by demonstrating that the device has the same intended use and similar technological characteristics (material, form, sizes, thickness, physical integrity, permeability, conformability) to a legally marketed predicate device. The "ground truth" for equivalence is the predicate device's established safety and effectiveness profile.

8. The sample size for the training set

This is not an AI/ML device. Therefore, there is no "training set" in the context of machine learning.

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

This is not an AI/ML device. There is no training set for this type of device.

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