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This product is intended to supply CO2 gas and feed water to clean lenses in the gastrointestinal tract when used as an accessory with Fujifilm's endoscopy system.

FUJIFILM Endoscopic CO2 Regulator GW-100 supplies CO2 gas to insufflate the gastrointestinal tract. The GW-100 supplies water to wash the endoscope lens during an examination.

FUJIFILM Endoscopic CO2 Regulator GW-100 is comprised of the following components: Main Unit, Water Tank, and Gas Tube. The Main Unit utilizes a solenoid/decompression valve mechanism to dispense CO₂ from the Water Tank via the Gas Tube and the air/water channel in the endoscope into the body cavity. The Main Unit also supplies sterile water Tank via the air/water channel in the endoscope.

The provided text describes a 510(k) premarket notification for the FUJIFILM Endoscopic CO2 Regulator GW-100. This document focuses on demonstrating substantial equivalence to a previously cleared predicate device, rather than proving that an AI/ML powered device meets specific performance criteria.

Therefore, the information required to answer the prompt (acceptance criteria, study details for an AI/ML device, sample sizes, expert involvement, etc.) is not present in this document. This document is for a medical device (a CO2 regulator for endoscopy) that is an accessory and does not appear to involve AI/ML.

The "Performance Data" section (Page 5) describes engineering and safety tests for the device itself and its accessories, not clinical performance or diagnostic accuracy. It mentions:

• Electrical safety testing: ANSI/AAMI ES60601-1, IEC 60601-1-2, IEC 60601-1-6, IEC 60601-2-18.
• Biocompatibility testing: ISO 10993-1, ISO 10993-5, ISO 10993-10 for an optional accessory.
• Software testing: IEC 62304 (for the predicate device, with the proposed device adopted into it).
• Cleaning, high-level disinfection, and sterilization validation testing: Per FDA guidance.
• "Performance testing" on CO2 gas supply and Water supply: Stated that "In all cases, the device met the pre-defined acceptance criteria for the test" but does not specify the criteria or the results.

Since the requested information pertains to AI/ML device performance and clinical validation, and this document describes a hardware medical device's engineering and safety testing for substantial equivalence, a complete answer to your prompt cannot be generated from the given input.

However, if we assume, for the sake of demonstrating the structure of the answer you're looking for, that the "CO2 gas supply" and "Water supply" tests were the "performance tests" for this device, a highly speculative and incomplete answer based on the limited provided text would look like this:

Based on the provided document, the device in question (FUJIFILM Endoscopic CO2 Regulator GW-100) is a hardware medical device, not an AI/ML powered device. As such, the comprehensive details typically required for AI/ML device validation (e.g., ground truth establishment, reader studies, effect sizes) are not applicable or provided in this 510(k) submission.

The document states that "performance testing" was conducted for "CO2 gas supply" and "Water supply," and that "In all cases, the device met the pre-defined acceptance criteria for the test." However, the document does not specify what these criteria were or the actual reported device performance values for these parameters.

Therefore, most of the specific questions regarding AI/ML device validation cannot be answered from this document.

1. Table of Acceptance Criteria and Reported Device Performance

Note: The document only states that the device "met the pre-defined acceptance criteria" but does not explicitly list the criteria or the quantitative results of the performance.

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

• Sample Size: Not specified for the "CO2 gas supply" and "Water supply" performance tests. This would typically involve engineering test units rather than patient data.
• Data Provenance: Not applicable in the context of clinical data for AI/ML. The tests are engineering/device performance tests.

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

• Not applicable. Ground truth as typically defined for AI/ML (e.g., diagnosis, abnormality detection) is not established for this type of device's performance testing. The "ground truth" for the performance tests would be the accurate measurement of CO2 gas and water supply.

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

• Not applicable. This is not a study requiring human adjudication of clinical data.

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. This is not an AI-powered device, and therefore, no MRMC study was conducted.

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

• Not applicable. This is not an AI-powered device.

7. The type of ground truth used:

• For the "CO2 gas supply" and "Water supply" tests, the "ground truth" would be the engineering specifications and calibrated measurement of the device's output, rather than clinical outcomes or expert consensus.

8. The sample size for the training set:

• Not applicable. This is not an AI/ML device that requires a "training set."

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

• Not applicable. This is not an AI/ML device.

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