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The Canady Flex RoboWrist is intended for grasping, mobilization, transection, suturing, and/or electrocautery of tissue under direct and endoscopic visualization.

The Canady Flex RoboWrist is a motorized, hand-held laparoscopic surgery instrument available with hook, scissors, or needle holder end-effectors. The device includes a connector for an electrosurgical generator, which allows the option of using the mono scissors or hook for electrosurgery. The Canady Flex RoboWrist primarily intended for dissection, and/or suturing of tissue under direct and endoscopic visualization in minimally invasive surgical procedures for interventions such as laparoscopic (urologic, gynecologic) or thoracic surgeries.

The Canady Flex RoboWrist is composed of an instrument (with end-effectors) and a control unit, which provides power to the instrument. Three models of instruments are available: needle-holder, monopolar hook and monopolar scissors. An electrical cable is provided to connect the instrument to the control unit. It is also provided with a sterilization tray.

The provided text is a 510(k) summary for the Canady Flex RoboWrist, an endoscopic instrument. This document describes the device, its intended use, and how it demonstrates substantial equivalence to a predicate device. However, it does not include detailed acceptance criteria or a study that evaluates the device's performance against specific clinical or diagnostic metrics, as would be expected for an AI/ML-driven device with performance claims.

Instead, the document focuses on non-clinical performance data to demonstrate safety and effectiveness for a surgical instrument. The key takeaway is that this is not an AI/ML device and therefore the questions about AI-specific performance criteria, ground truth, expert adjudication, and MRMC studies are not applicable.

Here's an analysis based on the provided text, highlighting what is present and what is not:

1. A table of acceptance criteria and the reported device performance

The document does not specify quantitative acceptance criteria in the typical sense for a medical device with performance metrics (e.g., sensitivity, specificity, accuracy). Instead, it lists various non-clinical tests that were performed to evaluate conformance to product specifications.

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

Not applicable. The "test set" here refers to physical components of the device and its performance in a lab setting, not a dataset of patient images or clinical outcomes.

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 applicable. This device is an endoscopic surgical instrument, not an AI/ML diagnostic or prognostic tool. "Ground truth" for this device would relate to engineering specifications, material properties, and functionality demonstrations performed by engineers and technicians, not clinical experts establishing diagnostic accuracy.

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

Not applicable. There is no clinical test set requiring adjudication in the context of an AI/ML 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

No. This is not an AI/ML-assisted device.

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

No. This is a surgical instrument operated by a human.

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

For the non-clinical tests, the "ground truth" is defined by the requirements and specifications of the referenced ISO and IEC standards (e.g., a material is cytotoxic or not based on ISO 10993-5 criteria; electrical safety is met if measurements are within IEC 60601-1 limits). For functionality, it's whether the device can successfully manipulate, cut, and suture tissue as intended.

8. The sample size for the training set

Not applicable. This device does not involve a training set as it is not an AI/ML device.

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

Not applicable. No training set is involved.

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