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The Disposable surgical face mask is intended to be worn to protect both the patient and healthcare personnel from transfer of microorganisms, body fluids, and particulate materials in infection control practices to reduce the potential exposure to blood and body fluids. This is a single use, disposable device(s), provided non-sterile.

The proposed device is blue color, and Flat Pleated type mask, utilizing Ear Loops way for wearing, and they all have Nose Piece design for fitting the facemask around the nose.

The proposed device is manufactured with three layers, the inner and outer layers are made of spun-bond Nonwoven fabric polypropylene, and the middle layer is made of melt blown polypropylene filter. The filter fiber is used for particle adsorption, mechanical sieve retention, inertial deposition, and electrostatic adsorption deposition, so that the air containing harmful substances is filtered through the filter material of the mask and then inhaled or exhaled.

The style of the device, ear loops, is held in place over the users' mouth and nose by two ear loops welded to the facemask. The ear loops are not made with natural rubber latex but made of polyester and spandex.

The nose piece contained in the proposed device is in the layers of facemask to allow the user to fit the facemask around their nose, which is made of polypropylene and iron.

The proposed device should be stored in a dry, ventilated and pollution-free area; the temperature should be 0-40 ℃, and the humidity should not be higher than 80%; Keep away from fire sources, avoid dust exposure and direct sunlight.

The proposed device is sold non-sterile and is intended to be a single use, disposable device.

The provided text is a 510(k) summary for a disposable surgical face mask. It does not detail a study involving AI assistance for human readers or the establishment of ground truth by multiple experts for an AI device. Instead, it focuses on demonstrating substantial equivalence of the new medical device (a surgical mask) to a legally marketed predicate device through non-clinical performance testing and biocompatibility studies.

Therefore, most of the requested information regarding AI device acceptance criteria, MRMC studies, ground truth establishment for AI, and training/test set details for an AI model cannot be extracted from this document as it pertains to a different type of medical device evaluation.

However, I can provide information based on the performance testing of the surgical mask, interpreted as its "acceptance criteria" and "device performance".

Here's the information that can be extracted:

Device Acceptance Criteria and Performance (for a Disposable Surgical Face Mask)

The acceptance criteria and performance data are based on non-clinical testing against established standards for medical face masks and biocompatibility.

1. Table of Acceptance Criteria and Reported Device Performance

The device (Disposable surgical face mask, Model: AD-PR02, AD-PR02-2, AD-PR02-S01, AD-PR02-S02 manufactured by Shandong Aida Medical Products Co., Ltd) was tested against the requirements for an ASTM F2100-2020 Level 2 classification mask.

2. Sample Size Used for the Test Set and Data Provenance

The sample sizes for specific tests are not uniformly detailed:

• Resistance to Penetration by Synthetic Blood: 32 samples were tested.
• Other performance tests (PFE, BFE, Differential Pressure, Flame Spread): Specific sample sizes are not explicitly mentioned, but the results are reported as meeting the criteria for the product.
• Biocompatibility tests (Cytotoxicity, Irritation, Sensitization): Standard test methods (ISO 10993) would dictate the sample sizes for these biological evaluations, but specific numbers are not provided in the summary.

Data Provenance: The tests were conducted by Shandong Aida Medical Products Co., Ltd, located in China. The data were collected retrospectively as part of the 510(k) submission process to demonstrate equivalence to a predicate device.

3. Number of Experts Used to Establish Ground Truth and Qualifications of Experts

This information is not applicable to this document as the device being assessed is a physical medical device (surgical mask), not an AI/software device that requires expert-established ground truth for image or data interpretation. The "ground truth" here is defined by performance standards and laboratory test results.

4. Adjudication Method for the Test Set

This is not applicable for the type of device and testing described. Adjudication methods (e.g., 2+1, 3+1) are typically used in clinical studies or expert reviews for AI/diagnostic devices to resolve discrepancies. The performance tests for a surgical mask are based on objective measurements against defined standards.

5. If a multi-reader multi-case (MRMC) comparative effectiveness study was done

No, an MRMC comparative effectiveness study was not done. This type of study is relevant for evaluating the impact of AI on human reader performance in diagnostic tasks, which is not applicable to a surgical mask.

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

This is not applicable. This question pertains to AI algorithm performance.

7. The type of ground truth used

The "ground truth" for this device's performance is established by objective laboratory test methods and international/national standards (e.g., ASTM F2100, ASTM F2101, EN 14683, ASTM F1862, ASTM F2299, 16 CFR Part 1610, ISO 10993). These standards define the acceptable performance metrics for properties like filtration efficiency, fluid resistance, breathability, flammability, and biocompatibility.

8. The sample size for the training set

This is not applicable. There is no "training set" in the context of this 510(k) submission, as it does not involve an AI algorithm that learns from data.

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

This is not applicable for the same reason as above.

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