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510(k) Data Aggregation
(272 days)
KJ ZIRCONIA Implant System
The KJ ZIRCONIA Implant System is intended to use in the treatment of missing teeth to support prosthetic device, such as artificial teeth, in order to restore mastication in partially edentulous patients. It is for delayed loading.
KJ ZIRCONIA Implant System is a dental implant system made of ZIRCONIA intended to be surgically placed in the bone of the upper or lower jaw arches. It is one piece type implant which the implant and the abutment are manufactured as one piece. It offers two types: BL type and BS type, and the difference is only in the length of the abutment part.
This document is a 510(k) Premarket Notification from the FDA for a dental implant system. It primarily focuses on demonstrating substantial equivalence to previously marketed devices rather than presenting performance data from a clinical or algorithm-based study for an AI/ML device. Therefore, it does not contain the information needed to answer your request about acceptance criteria and study proving performance for an AI/ML device.
Here's why the document doesn't provide the requested information:
- Device Type: The "KJ ZIRCONIA Implant System" is a physical medical device (a dental implant), not an AI/ML software device.
- Regulatory Pathway: A 510(k) submission for this type of device typically demonstrates equivalency to existing predicate devices based on design, materials, and intended use, supported by non-clinical testing (e.g., sterilization, biocompatibility, mechanical properties). It does not usually involve clinical performance studies in the way an AI/ML diagnostic or prognostic device would.
- Absence of AI/ML Specifics: There is no mention of algorithms, machine learning models, test sets, ground truth establishment by experts, or MRMC studies, which are all pertinent to evaluating AI/ML product performance.
Therefore, I cannot extract the requested information (acceptance criteria table, sample size, expert qualifications, adjudication, MRMC study, standalone performance, ground truth types, training set details) from this document as it pertains to an AI/ML device.
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