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The Disposable Procedural Ear-loop Face Mask is intended to be worn to protect both the patient and healthcare personnel from transfer of microorganisms, body fluids and particulate material. These face masks are intended for use in infection control practices to reduce the potential exposure to blood and body fluids. This a single use, disposable device(s), provided non-sterile.

The proposed device(s) are Blue color, and Flat Pleated type mask, utilizing Ear Loops way for wearing, and they all has Nose clips design for fitting the face mask around the nose. The proposed device(s) are manufactured with three layers, the inner and outer layers are made of spun-bond polypropylene, and the middle layer is made of melt blown polypropylene filter. The model of proposed device, ear loops, is held in place over the users' mouth and nose by two elastic ear loops welded to the face mask. The elastic ear loops are made of nylon and Dacron. The nose piece contained in the proposed device(s) is in the layers of face mask to allow the user to fit the face mask around their nose, which is made of polypropylene and iron. The proposed device(s) are sold non-sterile and are intended to be single use, disposable device.

The provided text is a 510(k) summary for a medical device (Disposable Procedural Ear-loop Face Mask) and focuses on demonstrating substantial equivalence to a predicate device. It contains information about non-clinical testing to support this claim, but it does not describe an AI/ML powered device or the types of studies typically conducted for such devices (e.g., studies involving human readers, ground truth establishment by experts, analysis of AI performance metrics like sensitivity/specificity).

Therefore, I will extract information related to the performance of the device as tested in the provided document, but many of the requested points regarding AI/ML powered device studies cannot be answered from this text.

Here's an analysis based on the provided document:

1. Table of acceptance criteria and the reported device performance

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

• Sample Size for performance tests: For Fluid Resistance, Particulate Filtration Efficiency, Bacterial Filtration Efficiency, and Differential Pressure, the testing involved 3 non-consecutive lots, with a sample size of 32 per lot.
• Data Provenance: The document does not explicitly state the country of origin of the test data or if the tests were conducted retrospectively or prospectively. The applicant is based in China. The tests are non-clinical laboratory tests.

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)

This is a non-clinical device (face mask). Ground truth, in the context of an AI/ML device for medical image analysis or similar, is not applicable here. The "ground truth" for this device's performance is established by standardized laboratory testing against defined physical and biological criteria.

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

Not applicable for a non-clinical device and laboratory performance tests.

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

Not applicable. This document describes a physical medical device (face mask), not an AI/ML powered device that would involve human readers or comparative effectiveness studies with AI assistance.

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

Not applicable. This is not an algorithm-only device.

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

The "ground truth" for this device's performance is based on established international and national standards for medical face masks and biocompatibility, as outlined in the following tests:

• ASTM F1862 (Fluid Resistance)
• ASTM F2299 (Particulate Filtration Efficiency)
• ASTM F2101 (Bacterial Filtration Efficiency)
• EN 14683 Annex C (Differential Pressure)
• 16 CFR 1610 (Flammability)
• ISO 10993-5 (Cytotoxicity)
• ISO 10993-10 (Irritation and Skin Sensitization)

These standards define the methodologies and acceptable performance values that constitute "ground truth" for compliance.

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 that requires a training set or ground truth for training.

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