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The Contact Detach™ is indicated for the infusion of fluids into the body below the surface of the skin when attached to a fluid reservoir.

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The provided text does not contain detailed acceptance criteria or a study that proves the device meets those criteria in the way typically expected for an AI/algorithm-driven device. This document is a 510(k) summary for a medical device (subcutaneous infusion set), not a software or AI product. As such, the information requested in the prompt (e.g., sample sizes for test/training sets, expert ground truth, MRMC studies) is largely irrelevant to this type of device submission.

However, I can extract the relevant information based on the provided text, while also noting what is not applicable.

Here's a breakdown of the information and what is not available from the text:

1. Table of Acceptance Criteria and Reported Device Performance

2. Sample size used for the test set and the data provenance

• Sample size: Not specified. The document states "Verifications testing has confirmed the product meets their specifications," but does not detail the sample sizes used for this testing.
• Data provenance: Not applicable in the context of AI/algorithm testing. The "testing" referred to is likely engineering and performance testing for a physical medical device.

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

• Not applicable. This is not an AI/algorithm-driven device where expert ground truth interpretation is typically required for image or data analysis. The "ground truth" for a physical device would relate to engineering specifications and physical performance.

4. Adjudication method for the test set

• Not applicable. No adjudication method is mentioned or relevant to the nature of this physical device's testing.

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

• No. This is not an AI/algorithm-driven device; therefore, an MRMC study comparing human readers with and without AI assistance is irrelevant and was not performed.

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

• No. This is not an AI/algorithm-driven device.

7. The type of ground truth used

• The "ground truth" for this medical device would be based on engineering specifications and physical performance measurements rather than expert consensus, pathology, or outcomes data in the context of diagnostic interpretation. The document broadly states "Verifications testing has confirmed the product meets their specifications."

8. The sample size for the training set

• Not applicable. This is not an AI/algorithm-driven device and therefore does not have a "training set" in the machine learning sense.

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

• Not applicable. This is not an AI/algorithm-driven device.

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