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The BellaTek Encode Emergence Healing Abutments are intended for use as an accessory to endosseous dental implants during endosseous and gingival healing to prepare gingival tissue for acceptance of a final abutment and restoration.

The BellaTek Encode Emergence Healing Abutment is a two-piece healing abutment (abutment with a retaining screw) designed to facilitate gingival tissue healing before a final restoration is placed. It consists of an abutment and a retaining screw that are assembled and packaged together and provided sterile. Both components are machined from Titanium Alloy Ti-6Al-4V ELI (ASTM F136). They are available in pre-defined diameters, emergence profiles and heights to accommodate varying patient anatomies. The shelf life of the TSV BellaTek Encode Healing Abutment is 5 years from the date of manufacture and they are intended for single use only. The device is packaged in a blister tray with Tyvek Lid and sold sterile. The device is sterilized using the gamma irradiation method. The BellaTek Encode Emergence Healing Abutments are color anodized for aesthetic purposes.

This document is a 510(k) Premarket Notification from the FDA regarding the "BellaTek Encode Emergence Healing Abutments". It does not describe an AI/ML device, therefore the requested information regarding acceptance criteria and study details for AI/ML performance is not present.

The document focuses on demonstrating substantial equivalence to previously approved predicate devices, rather than an AI/ML device's performance.

Here's why the requested information cannot be extracted:

• No AI/ML Component: The device is a physical dental implant component (healing abutment), not a software algorithm or AI-powered system.
• Substantial Equivalence: The approval process here is based on showing that the new device is as safe and effective as a legally marketed predicate device, not on meeting specific performance metrics for an AI algorithm.
• Non-Clinical Testing: The "Non-Clinical Testing" section describes tests related to physical properties, biocompatibility, sterilization, and shelf-life, which are typical for physical medical devices. It does not mention any studies related to AI/ML performance metrics like accuracy, sensitivity, specificity, etc.

Therefore, since the input document describes a physical medical device and not an AI/ML device, it does not contain the information requested in the prompt about AI/ML acceptance criteria and study details.

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