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The Unimax Laparoscopic Instrument is a family of instruments which includes forceps, scissors, and probes which are intended to be used in general laparoscopic surgical procedures requiring the use of Monopolar electrosurgical cutting and/or coagulation.

The Unimax Laparoscopic Instrument includes Grasping Forceps, Monopolar Scissors, and Monopolar Probe/Electrodes. The devices are disposable, single use, individually packaged devices that are composed of biocompatible materials. Scissors and forceps have a handle with rotating wheel attached to an insulated shaft with different tips, which allows the shaft and tip to rotate. They include a male cautery connector when attached to standard monopolar cautery cables and their generators. Probes/Electrodes have an insulated shaft with a thermally conductive metal tip electrode. The proximal end of the shaft is attached to a handle made of an injection molded, medical grade plastic.

The provided text describes a 510(k) summary for the Unimax Laparoscopic Instrument, and it focuses on demonstrating substantial equivalence to a predicate device rather than presenting a standalone study with specific performance acceptance criteria for an AI device.

Therefore, many of the requested items (e.g., sample sizes for test sets and training sets, number of experts for ground truth, adjudication method, MRMC studies, standalone AI performance) are not applicable to this document as it pertains to a traditional medical device (surgical instruments) and not an AI/ML-driven device.

However, I can extract the relevant information regarding performance testing and acceptance criteria for this specific device.

1. Table of Acceptance Criteria and Reported Device Performance

The document states that the comparative performance testing included the items listed below and that "All the test results demonstrate the performance of Unimax Laparoscopic Instrument meets the requirements of its pre-defined acceptance criteria and intended uses." Specific numerical acceptance criteria are not detailed in this summary. Instead, it relies on demonstrating equivalence to the predicate device.

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

Not applicable. This is not an AI/ML device study. The testing was physical and mechanical bench testing, as well as biocompatibility and electrical safety. The document does not specify sample sizes for these tests, nor data provenance in terms of country of origin of data or retrospective/prospective study, as these concepts are generally tied to clinical data or AI model development.

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/ML device that requires experts to establish ground truth from clinical images or data. The "ground truth" here is the performance metrics defined by engineering standards and industry best practices for surgical instruments.

4. Adjudication method for the test set

Not applicable. No expert adjudication method (like 2+1, 3+1) is mentioned or relevant for the type of bench testing conducted for this device.

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. This document describes a traditional laparoscopic instrument, not an AI-assisted device. Therefore, no MRMC study comparing human readers with and without AI assistance was conducted.

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

Not applicable. There is no algorithm or AI component in this device, so standalone algorithm performance testing is not relevant.

7. The type of ground truth used

For the physical, mechanical, electrical safety, and biocompatibility tests, the "ground truth" is defined by adherence to recognized international standards and engineering specifications (e.g., IEC 60601 series, ISO 10993 series, ISO 11135-1) and comparison with the predicate device's established performance. It's not clinical "outcomes data" or "pathology" in the typical sense for AI devices, but rather objective measurements and compliance with regulatory and engineering benchmarks.

8. The sample size for the training set

Not applicable. This device does not involve a training set for an AI/ML model.

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

Not applicable. There is no AI/ML training set for this device.

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