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The Uni/Monopolar High Frequency Cables are used to connect adequately equipped R. Wolf HF instruments to the corresponding HF devices.

The Uni/Monopolar HF Cables are used to direct a high frequency electrical current from an electrical generator made by unspecified manufacturers to a R. Wolf HF instrument.

The provided document does not describe an AI/ML device or a study with typical acceptance criteria as would be found for such a device. Instead, it is a 510(k) summary for a Uni/Monopolar HF Cable, a medical instrument component.

Therefore, most of the requested information regarding AI/ML device performance, sample sizes, ground truth establishment, MRMC studies, or standalone algorithm performance cannot be extracted from this document.

Here's an analysis of what is available, and why other sections are not applicable:

Acceptance Criteria and Reported Device Performance

The document states:

• "No known FDA performance standard exists."
• "The Monopolar HF Cables were tested to comply with the appropriate sections of ANSI/AAMI standard on high frequency devices, HF18 and IEC601-2-18."
• "The devices are designed and tested to guarantee the safety and effectiveness when used according to the instruction manuals."

Given the nature of the device (a cable), the acceptance criteria are not presented in a table format with specific performance metrics like sensitivity, specificity, or AUC, as would be expected for an AI/ML diagnostic or prognostic tool. Instead, the acceptance criteria are compliance with recognized electrical safety and performance standards for high-frequency medical devices.

Table of Acceptance Criteria and Reported Device Performance (Best Effort based on available information):

1. Sample sizes used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

• Not Applicable / Not Provided. This document describes testing for an electrical cable against engineering standards, not a study involving patient data or a test set in the context of AI/ML evaluation. There is no mention of a "test set" in this context.

2. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)

• Not Applicable. Ground truth, in the AI/ML sense, is not established for this device evaluation. The "ground truth" for a cable would be its adherence to electrical and material specifications, which are verified through engineering tests, not expert consensus on medical images or clinical outcomes.

3. Adjudication method (e.g. 2+1, 3+1, none) for the test set

• Not Applicable. There is no "test set" and no human expert adjudication as understood in AI/ML validation studies.

4. 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 a hardware component (a cable), not an AI/ML system. There are no human readers or AI assistance involved in its evaluation as described.

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

• Not Applicable. This is a physical, non-algorithmic device.

6. The type of ground truth used (expert consensus, pathology, outcomes data, etc.)

• Technical Specifications and Engineering Standards. The "ground truth" for this device's performance is adherence to defined technical specifications (e.g., maximum voltage, sterilization capacity) and compliance with electrical safety standards (ANSI/AAMI HF18 and IEC601-2-18).

7. The sample size for the training set

• Not Applicable. This is a hardware component; there is no "training set" as it does not involve machine learning.

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

• Not Applicable. As there is no training set, this question is irrelevant.

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