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The OSSTEM Abutment System is intended for use with a dental implant to provide support for prosthetic restorations such as crowns, bridges, or overdentures.

Osstem Abutment System is compatible with the following implant systems.
Osstem Implant Co., Ltd. TS SA Fixture Internal Hex 3.2, 3.5, 3.75, 3.77, 4.2, 4.25, 4.4, 4.6, 4.63, 4.65, 4.8, 4.9, 5.05, 5.08, 5.1, 5.25, 5.92, 5.95, 6, 6.2, 6.8, 7.1
Osstem Implant Co., Ltd. US SA Fixture External Hex 3.6, 4.2, 5.1, 5.2
Osstem Abutment System is intended for use with a dental implant to provide support for prosthetic restorations such as crowns, bridges, or overdentures.
Osstem Abutment System is similar to other commercially available products based on the intended use, technology used, claims, material composition employed and performance characteristics.
Osstem Abutment System is substantially equivalent in design, function and intended use to the predicate devices as above.

The provided text is a 510(k) Summary for the Osstem Abutment System, which aims to demonstrate substantial equivalence to previously cleared predicate devices. It does not contain information related to an AI/ML-driven medical device, nor does it conduct a study measuring medical device performance against specific acceptance criteria in the manner one would see for an AI/ML model for diagnostic or prognostic purposes.

The document discusses non-clinical performance testing to support substantial equivalence, primarily focusing on materials, design, and mechanical properties (fatigue testing). It explicitly states:

• "Non-clinical testing data are submitted to demonstrate substantial equivalence." (Page 10)
• "No clinical studies are submitted." (Page 11)

Therefore, I cannot fulfill the request as it asks for information typically found in submissions for AI/ML-driven diagnostic devices, such as:

• A table of acceptance criteria and reported device performance (in terms of clinical metrics like sensitivity, specificity, AUC)
• Sample sizes for test sets, data provenance
• Number of experts and their qualifications for ground truth
• Adjudication methods
• MRMC comparative effectiveness study results
• Standalone performance
• Type of ground truth
• Training set sample size and ground truth establishment

The document presents a comparison to predicate devices, stating that new dimensions or minor design changes are not considered "worst-case" for fatigue given existing predicate device testing, thus negating the need for additional testing in some instances. It relies on the substantial equivalence principle, which means the device is as safe and effective as a legally marketed device.

In summary, the provided text does not contain the specific information required to answer your detailed questions about acceptance criteria, study design, and performance metrics for an AI/ML device.

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