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The Intuitive Surgical™ Endoscopic Instrument Control System (hcreinafter referred to as the "da Vinci™ System") is intended to assist in the accurate control of Intuitive Surgical™ endoscopic instruments including: rigid endoscopes, blunt and sharp endoscopic dissectors, scissors, scalpels, forceps / pick-ups, needle holders, endoscopic retractors, stabilizers, electrocautery and accessories during laparoscopic surgical procedures such as cholecystectomy or Nissen fundoplication. It is intended for use by trained physicians in an operating room environment.

Intuitive Surgical™ Endoscopic Instruments including scissors, scalpels, forceps/pickups, needle holders, clip appliers, and electrocautery are intended for endoscopic manipulation of tissue, including: grasping, cutting, blunt and sharp dissection, approximation, ligation, electrocautery and suturing .

The working ends and elements of the Intuitive Surgical™ Endoscopic Instruments and Accessories are essentially identical in size and shape to the predicate devices referenced and represent standard embodiments of standard surgical tools modified for use with the Intuitive Surgical™ Endoscopic Instrument Control System.

The provided text describes a 510(k) submission for the Intuitive Surgical™ Endoscopic Instrument Control System and Endoscopic Instruments. This submission focuses on establishing substantial equivalence to predicate devices, rather than presenting a study to meet specific quantitative acceptance criteria for device performance. Therefore, many of the requested sections about quantitative acceptance criteria, detailed study design, and advanced statistical analyses (like MRMC) are not explicitly present in the provided document.

Here's an attempt to extract and infer the information based on the given context:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not specify quantitative acceptance criteria (e.g., specific thresholds for accuracy, sensitivity, or specificity) or numerical reported device performance metrics. The core of the submission is based on demonstrating "substantial equivalence" to predicate devices, which is a qualitative assessment rather than a quantitative one against predefined statistical targets.

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

The document states an "extensive prospectively randomized and concurrently controlled clinical study was performed." However, it does not provide the specific sample size for this clinical study or details on the data provenance (e.g., country of origin). The study is prospective, as indicated by "prospectively randomized."

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

This information is not provided in the document. As the study focuses on safety and effectiveness compared to predicate devices in surgical procedures, the "ground truth" would likely be based on clinical outcomes assessed by the operating surgeons and medical staff, rather than a separate panel of experts establishing a ground truth for a diagnostic task.

4. Adjudication method for the test set

This information is not provided.

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

The document describes a "prospectively randomized and concurrently controlled clinical study" to demonstrate substantial equivalence in terms of safety and effectiveness. However, it does not explicitly state that this was an MRMC comparative effectiveness study focused on comparing human readers' performance with and without AI assistance. The Intuitive Surgical Endoscopic Instrument Control System is a surgical robotic system, not a diagnostic AI system, so the concept of "human readers" improving with "AI assistance" in the typical diagnostic sense does not directly apply here. The study would have compared clinical outcomes with the new device versus predicate devices.

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

No, this device is explicitly described as an "Endoscopic Instrument Control System" intended "to assist in the accurate control of Intuitive Surgical™ Endoscopic Instruments." It is an assistive surgical tool, inherently designed for human-in-the-loop performance, not a standalone algorithm.

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

Given it's a clinical study for a surgical instrument, the "ground truth" for safety and effectiveness would implicitly be based on clinical outcomes data (e.g., successful procedure completion, complication rates, recovery times, surgeon's assessment of ease of use and tissue effect) observed and documented during the "prospectively randomized and concurrently controlled clinical study."

8. The sample size for the training set

This information is not applicable and not provided. The device is a surgical instrument control system, not an AI model that requires a training set in the conventional machine learning sense. The "design analysis and comparison" and "in vitro testing" would be validated against engineering specifications and functional requirements, not a training set.

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

This information is not applicable and not provided, as there is no mention of a training set for an AI model.

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