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The endoscope system is used to examine body cavities, hollow organs and canals, specifically the lower GI tract (colon) only, and, using additional accessories, to perform various diagnostic and therapeutic procedures.

The endoscope system includes the endoscope with control head, a disposable assembly, an imaging system, and a fluid and air system. The endoscope system features: 1) a smooth control head containing a minimal number of outside angles and joint crevices, 2) a single use disposable system encompassing all of the inner passage channels that start at the manifold, continue through the endoscope cavity, and seal onto the outside of the rigid distal tip, 3) a pneumatically driven air and fluid system eliminating the need for mechanical valves in the contamination path, and 4) a lavage function that provides a bolus of water through the working channel to loosen and flush debris from the field of view as the insertion tube advances through the colon.

The provided text is a 510(k) premarket notification for an endoscope system. It details the device's description, indications for use, and a comparison to predicate devices, but it does not contain information about specific acceptance criteria, performance studies, sample sizes, ground truth establishment, or expert involvement.

The document states that the device is "substantially equivalent" to predicate devices, which is the basis for its clearance, rather than proof of meeting specific performance acceptance criteria through independent studies.

Therefore, most of the requested information cannot be extracted from the provided text.

Here is what can be inferred or stated based on the given information:

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

The document does not explicitly state acceptance criteria or report specific device performance metrics in the way that would typically be seen in a clinical study. Instead, it compares the physical and functional specifications of the akos endoscope system to several predicate devices.

Note: The "acceptance criteria" here are inferred from the comparison to predicate devices, implying that performance within the range of existing, legally marketed devices for similar specifications is deemed acceptable for substantial equivalence. No specific quantitative performance targets (e.g., image resolution, diagnostic accuracy) are provided in the document.

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

• No information available. The document does not describe a test set or clinical study with a specified sample size or data provenance. The clearance is based on substantial equivalence to predicate devices, not on a new clinical performance study.

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)

• No information available. There is no mention of a test set or ground truth established by experts within this document.

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

• No information available. There is no mention of a test set or adjudication method.

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 information available. This document is for a medical device (endoscope), not an AI-powered diagnostic system, and it predates widespread AI application in this context (1997). No MRMC study or AI assistance is mentioned.

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

• Not applicable. This device is an endoscope system, which is a tool used by a human operator for examination and procedures. It is not a standalone algorithm.

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

• No ground truth discussed. The 510(k) submission primarily focuses on engineering specifications and intended use comparison to predicate devices for substantial equivalence, not on establishing a ground truth for diagnostic accuracy.

8. The sample size for the training set

• Not applicable. This document describes a physical medical device, not a machine learning model, so there is no concept of a "training set" in this context.

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

• Not applicable. As above, no training set or ground truth for it is relevant to this device's submission.

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