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The VisionPort System is intended to be used in diagnostic and therapeutic for endoscopic surgery within the thoracic and peritoneal cavities including the female reproductive organs to establish a path of entry for endoscopic instruments and to provide an image of the surgical field. The trocar may be used with or without visualization for primary and secondary insertions.

The VisionPort System consists of an access port with an integrated camera and light source, the handpiece, a wired control pad to control the camera functions, and a control unit, specifically:

• 1. VisionPort System Handpiece single use
  • HD camera and lighting module a.
  • b. 12.9mm internal diameter access port with 5-12mm instrument seal
  • Lens cleaning system (saline wash and wiper blade) C.
  • d. Connections for saline wash source and insufflation tubing
  • e. Removable obturator designed for visible entry
• 2. VisionPort System Control Pad single use
  • a. Camera control functions (zoom, pan)
  • b. Light emitting diode (LED) adjustment
  • c. Image capture and display control buttons
• 3. VisionPort System Control Unit
  • a. System power
  • b. Image processing (no patient data recording or retention)
  • Outputs to operating room monitor(s) and/or third-party Data Control Unit (for image C. capture and printing options)

The provided text describes the VisionPort System, an endoscopic surgical device, and its substantial equivalence to predicate devices, but it does not contain information about acceptance criteria or a study proving that the device meets those criteria in the context of an AI/ML-assisted medical device.

The document is a 510(k) summary for a medical device (VisionPort System) to establish substantial equivalence with existing predicate devices. It focuses on the device's design, indications for use, and a comparison of its technological characteristics with predicate devices.

While it mentions "performance data" and "functional testing" to verify that the device met "all design specifications" and "acceptance criteria," these are general statements about the device's functionality rather than specific, quantitative acceptance criteria for an AI/ML component. The "functional testing" appears to be related to the physical and operational aspects of the endoscope and its components, referencing standards like ISO 8600.

Therefore, I cannot provide the requested information regarding acceptance criteria and a study proving an AI/ML component meets those criteria, as the document does not discuss such an AI/ML feature as part of the VisionPort System.

Here's why the requested information cannot be extracted from the provided text:

• No AI/ML Component: The device description and comparisons do not indicate the presence of artificial intelligence or machine learning components within the VisionPort System. It's an endoscopic system with a camera, light source, control pad, and control unit.
• No Quantitative Acceptance Criteria for AI/ML: Since there's no mention of an AI/ML component, there are no specific quantitative acceptance criteria (like sensitivity, specificity, AUC) for such a component.
• No Study Design for AI/ML Performance: Consequently, there is no study described that would prove an AI/ML component meets acceptance criteria. The performance data section refers to sterilization, biocompatibility, electrical safety, EMC, and functional testing of the physical device.

In summary, the provided document does not align with the premise of the question, which assumes an AI/ML-assisted medical device.

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