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Endoscopic Video Image Processor: This device is used in conjunction with the video endoscopes produced by our company to process the images collected by the video endoscopes and send them to the display, and provide power for the endoscope.
Single-Use Video Gastroscope: This product is used in conjunction with Endoscopic Video Image Processor and other peripheral equipment for the observation, diagnosis, photography and treatment of upper digestive tract. The device is suitable for professional healthcare facility environments such as hospitals and clinics. This product is designed for use in adults.
Single-Use Video Colonoscope: This product is used in conjunction with Endoscopic Video Image Processor and other peripheral equipment for the observation, diagnosis, photography and treatment of lower digestive tract. The device is suitable for professional healthcare facility environments such as hospitals and clinics. This product is designed for use in adults.

The proposed device, Digestive Endoscopy System, which includes a Single-Use Video Gastroscope and Single-Use Video Colonoscope, and Endoscopic Video Image Processor is intended for observation, diagnosis, photography and treatment of the upper and lower gastrointestinal tract.
The Single-Use Video Gastroscope is available in two models with different length of image processor connection section, RP-Gl-G02A, RP-Gl-G02B. The Single-Use Video Colonoscope is available in two models with different length of image processor connection section and different diameters, RP-GI-C02B. The Endoscopic Video Image Processor is available in four models with disk space, RP-IPD-V2000A, RP-IPD-V2000B, RP-IPD-V2000C, RP-IPD-V2000D.
The Single-Use Video Gastrocope and Single-Use Video Colonoscope are sterile and single-patient-use device. The Endoscopic Video lmage Processor is non-sterile and multi-patient-use device, and it will be cleaned and disinfected before first use.

The provided text is a 510(k) summary for an Endoscopic Video Image Processor, Single-Use Video Gastroscope, and Single-Use Video Colonoscope. It does not contain information about acceptance criteria or a study proving the device meets them in the context of an AI/human performance study. The document primarily focuses on demonstrating substantial equivalence to a predicate device through non-clinical performance and comparison testing.

Therefore, for aspects like acceptance criteria for AI algorithms, sample size for test sets (in an AI context), expert details, adjudication methods, MRMC studies, standalone AI performance, and AI training set details, the information is not available in the provided text.

Based on the provided document, here's what can be extracted regarding performance testing, which is primarily focused on the device's functionality and image quality as an endoscopy system, rather than an AI component:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly present a table of "acceptance criteria" with numerical targets and reported performance values for an AI component. Instead, it describes various performance tests conducted. The implicit acceptance criterion for these tests is that the proposed device performs comparably to or meets the standards of the predicate device or relevant ISO standards.

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

This information is not available in the provided text. The "test set" in the context of this document refers to the physical devices (Endoscopic Video Image Processor, Single-Use Video Gastroscope, Single-Use Video Colonoscope) subjected to performance tests, not a dataset for an AI algorithm.

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

This information is not available in the provided text. The studies described are non-clinical engineering and performance tests, not clinical studies requiring expert ground truth for interpretation of medical images.

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

This information is not available in the provided text. Adjudication methods are typically employed in clinical image interpretation studies, which this document does not describe.

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

This information is not available in the provided text. The device described is an endoscope system, not an AI-assisted diagnostic tool.

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

This information is not available in the provided text. There is no mention of an algorithm or AI functionality in this submission.

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

This information is not available in the provided text. The "ground truth" for the non-clinical performance tests would be established by engineering specifications, calibration standards, and comparison with the predicate device.

8. The sample size for the training set

This information is not available in the provided text. The document does not describe an AI training set.

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

This information is not available in the provided text. The document does not describe an AI training set.

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