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510(k) Data Aggregation
(83 days)
DENTALIS KEZ ENDODONITC SEALER
For use in the sealing of prepared root canals in adult or decidious teeth prior to final filling with gutta percha or other acceptable root canal filler. Used to promote healing effects and to help prevent bacterial contamination of the canal.
Endodontic Sealer
The provided text is a clearance letter from the FDA for a medical device called "Dentalis Kez Endodontic Sealer" (K971642). It states that the device is substantially equivalent to a predicate device and can be marketed. However, this document does not contain specific acceptance criteria, details of a study proving the device meets those criteria, or any information related to AI or algorithm performance.
Therefore, I cannot provide the requested information. The document is a regulatory clearance and not a study report or clinical trial summary.
To clarify, the information I cannot extract from the provided text includes:
- A table of acceptance criteria and the reported device performance: This document only states the device is "substantially equivalent" for its indications for use. It does not list specific performance metrics or acceptance criteria.
- Sample size used for the test set and the data provenance: No study details are provided.
- Number of experts used to establish the ground truth for the test set and the qualifications of those experts: No study details are provided.
- Adjudication method for the test set: No study details are provided.
- 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 a physical dental sealer, not an AI or imaging device, so MRMC studies are not relevant. This document does not mention any AI component.
- If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not applicable as this is not an algorithm.
- The type of ground truth used: No study details are provided.
- The sample size for the training set: Not applicable as this is not an algorithm.
- How the ground truth for the training set was established: Not applicable as this is not an algorithm.
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