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The ATI-014 Insulation and Continuity Testing system is a non-destructive, non-patient contacting, voltage insulation tester designed to test the insulation of electrosurgical instruments.

The ATI 014FC Insulation and Continuity Tester and InsulScan Insulation Testing System have the same indications for use, basic design, both are battery operated battery operated and rechargeable.

The provided text describes a 510(k) premarket notification for an Insulation and Continuity Testing System. However, it does not include acceptance criteria, specific study designs, performance data (beyond general statements about equivalence), or details about ground truth establishment, sample sizes for training/testing, expert involvement, or adjudication methods.

Therefore, I cannot populate the requested table and answer the study-related questions based on the provided text. The document focuses on regulatory equivalence to a predicate device rather than presenting detailed performance studies.

Here's how I would answer each point given the lack of information:

Acceptance Criteria and Device Performance Study Information:

1. Table of acceptance criteria and the reported device performance:

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

• Sample Size (Test Set): Not specified in the provided text.
• Data Provenance: Not specified in the provided text.

3. 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 specified in the provided text. The submission relies on demonstrating equivalence to a predicate device rather than independent clinical or performance data with expert-adjudicated ground truth.

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

• Not applicable as no specific test set or expert adjudication process is described.

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:

• Not applicable. The device is an Insulation and Continuity Tester, not an AI-assisted diagnostic tool that would involve human readers or AI improvement metrics.

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

• The document implies standalone performance comparison to a predicate device, but no specific study details are provided. This is a device for testing insulation, not an AI algorithm.

7. The type of ground truth used (expert concensus, pathology, outcomes data, etc):

• Not specified. The basis for equivalence seems to be "basic design" and "indications for use" being the same as the predicate, rather than comparison against an established ground truth for instrument insulation issues.

8. The sample size for the training set:

• Not applicable/Not specified. This is a hardware device submission, not an AI/ML algorithm requiring a training set in the conventional sense.

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

• Not applicable. No training set is mentioned as this is not an AI/ML algorithm submission.

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