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The Medicon Epiplating System is indicated for the attachment of an external restoration prosthesis for restoration of a physical defect when other means of attachment are inadequate. The Epiplating system provides the bone anchorage for the prosthetic attachment. These devices are indicated for use in the maxillo-craniofacial region (including ear, nose and eye).

The Medicon Epiplating System is an implant system consisting of various plates used as the foundation for anchoring prostheses or epitheses in the craniofacial region. The system offers various implant sizes to fit the anatomical needs of a wide variety of patients. Components are manufactured from pure titanium (ASTM F67) or Ti6Al4V alloy (ASTM F136).

The provided text describes a 510(k) premarket notification for the "Medicon Epiplating System" and primarily focuses on demonstrating substantial equivalence to predicate devices, rather than presenting a study of its performance against specific acceptance criteria for an AI/ML-based device.

Therefore, most of the requested information regarding acceptance criteria, study details, sample sizes, expert involvement, adjudication, MRMC studies, standalone performance, and ground truth establishment cannot be found in the provided document.

The document is a regulatory submission for a physical medical device (an implant system), not an AI/ML software device. The "Performance Data" section discusses mechanical testing, sterilization validation, cleaning validation, and biocompatibility, which are standard for such devices, but not the type of performance metrics (e.g., sensitivity, specificity, AUC) typically associated with AI/ML solutions and their acceptance criteria.

Summary of what can be extracted based on the provided text:

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

• Not applicable/Not found. The document does not specify quantitative "acceptance criteria" in terms of clinical performance metrics that would be relevant for an AI/ML device (e.g., sensitivity, specificity). Instead, it refers to mechanical testing standards (ASTM F382) and biocompatibility standards (ISO 10993-1). The results are qualitative ("demonstrate substantial equivalence") rather than quantitative against specific clinical performance thresholds.

2. Sample sized used for the test set and the data provenance:

• Not applicable/Not found. This section is irrelevant for the type of device described. No "test set" of clinical data (images, patient records) is mentioned. "Performance data" refers to bench testing on the device itself.

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

• Not applicable/Not found. This information pertains to studies with human expert interpretation, typically in the context of AI/ML evaluation. This document describes a physical implant system.

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

• Not applicable/Not found. This is for clinical data interpretation, not for evaluating a physical implant.

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:

• Not applicable/Not found. This is specific to AI/ML devices that assist human readers.

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

• Not applicable/Not found. This is specific to AI/ML algorithm performance.

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

• Not applicable/Not found. For this physical device, "ground truth" would be related to material properties meeting standards, mechanical performance under specified loads, and biocompatibility, which are evaluated against established engineering and biological standards, not clinical ground truth derived from expert consensus or pathology.

8. The sample size for the training set:

• Not applicable/Not found. There is no AI/ML training set.

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

• Not applicable/Not found. There is no AI/ML training set.

Information that is mentioned in the document (but not directly addressing the AI/ML specific questions):

• Device Type: Medicon Epiplating System, an implant system.
• Purpose: Attachment of an external restoration prosthesis for physical defects in the maxillo-craniofacial region (ear, nose, eye).
• Regulatory Mechanism: 510(k) premarket notification.
• Substantial Equivalence: Demonstrated through comparison of technological characteristics (design, intended use, material composition, function) to predicate devices.
• Performance Data (for this device type):
  • Mechanical Testing: Performed in accordance with ASTM F382 (proof of load, bending strength, bending stiffness, structural bending stiffness).
  • Sterilization Validation: Pre-vacuum (steam) sterilization in accordance with ANSI/AAMI/ISO 17665-1:2006/(R)2013.
  • Cleaning Validation: Manual and machine cleaning validation in accordance with AAMI TIR30:2011.
  • Biocompatibility: Based on previously cleared devices with identical material and manufacturing methods, tested according to ISO 10993-1.

The document entirely pertains to a physical medical device and does not involve AI/ML technology, which is why the specific questions about AI/ML acceptance criteria and study design cannot be answered from the provided text.

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