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The O-Mec Laparoscopes 690 Series (Models, 90-331000H, 690-300500H, 690-300500H, are intended to be used by surgeons in diagnostic and therapeutic procedures. Laparoscopic minimally invasive procedures are performed in the abdominal cavity by means of small skin punctures that allow the insertion of the laparoscope and laparoscopic instruments.

O-Mec laparoscopes 690 Series Models 690- 331000H, 690-331030H, 690-300500H, 690-300530H are rigid endoscopes that are used to view a patient's internal anatomy for examination, diagnosis and therapy during laparoscopic procedures. An endoscope is a slender, tubular optical instrument used as a viewing system for examining an inner part of the body. The inside of the endoscope contains a series of lenses that transmit the endoscopic image, which is illuminated by an external light source.

O-Mec laparoscopes 690 Series Models 690- 331000H, 690-331030H, 690-300500H, 690-300530H are available in two sizes: 5mm or 10mm diameters, with either 0° or 30° directions of view. O-Mec laparoscope provides a high definition image and can correct chromatic aberration in the 400-900nm wavelength range.

O-Mec laparoscopes 690 Series Models 690- 331000H, 690-331030H, 690-300500H, 690-300530H are delivered non-sterile and are reusable and fully autoclavable. O-Mec laparoscopes must be cleaned according to the Instructions of Use before each use.

The provided text describes the O-Mec Laparoscopes 690 Series and its substantial equivalence to predicate devices, but it does not contain information related to AI/ML device performance, acceptance criteria for AI/ML, or studies explicitly designed to prove an AI/ML device meets such criteria.

The document is a 510(k) Pre-Market Notification for a traditional medical device (laparoscopes). The "acceptance criteria" discussed are for the physical and functional performance of the laparoscope itself (e.g., optical performance, sterilization validation, electrical safety) in comparison to predicate devices, not for an AI/ML algorithm's diagnostic or predictive capabilities.

Therefore, I cannot extract the requested information, such as:

1. A table of acceptance criteria and reported device performance for an AI/ML device.
2. Sample sizes used for test sets (for AI/ML), data provenance, etc.
3. Number of experts, qualifications, and adjudication methods for AI/ML ground truth.
4. MRMC comparative effectiveness study details (AI vs. human).
5. Standalone performance of an AI algorithm.
6. Type of ground truth used (for AI/ML).
7. Sample size for the training set (for AI/ML).
8. How ground truth for the training set was established (for AI/ML).

The document explicitly states: "Clinical testing was not performed with this device." and the "Summary of Non-Clinical Testing" focuses on hardware performance, cleaning, and safety. There is no mention of an AI/ML component or any associated performance metrics or studies.

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