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Disposable Medical Mask is intended to be worn to protect both the patient and healthcare personnel from transfer of microorganisms, body fluids and particulate material. It is intended for use in infection control practices to reduce the potential exposure to blood and body fluids. This is a single use, disposable device(s), provided as sterile.

The Disposable Medical Mask consists of a mask body, a nose piece, and ear loops or ties. The mask body is divided into four layers, the inner, second and outer layers are made of polypropylene materials; the middle layer is composed of melt-blown cloth (polypropylene); the nose piece is made of galvanized iron wire, the ear loops are made of polyester and spandex, and the ties are made of polypropylene. The Medical Surgical Mask will be provided in green. The Disposable Medical Mask is sold as sterile and are intended to be single use, disposable devices.

This document primarily details the non-clinical testing and substantial equivalence determination for a Disposable Medical Mask (K222545) in comparison to a predicate device (K211454). It is not a study that proves a device meets acceptance criteria through a clinical or reader study involving human interpretation of AI results.

This submission is for a medical mask, which is a physical device, and the "acceptance criteria" discussed are primarily related to its physical and biological performance characteristics (e.g., filtration efficiency, fluid resistance, biocompatibility), not the performance of an AI algorithm. Therefore, many of the requested points, such as those related to AI algorithm performance, human expert adjudication, MRMC studies, and ground truth establishment for AI training/testing, are not applicable to this document.

However, I can extract the relevant information regarding the acceptance criteria and performance of the mask itself based on the provided text.

Acceptance Criteria and Device Performance (Applicable to the physical mask device)

The document details the performance testing of the Disposable Medical Mask against established standards.

1. Table of Acceptance Criteria and Reported Device Performance

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

• Synthetic Blood Penetration: 32 samples (stated as "32 out of 32 pass at 160 mmHg"). For acceptance, it states "29 samples out of 32 pass (AQL 4%)".
• Other performance tests (Particulate Filtration Efficiency, Bacterial Filtration Efficiency, Differential Pressure, Flammability, Biocompatibility): Specific sample sizes are not explicitly stated for each test, but standard test methods (e.g., ASTM, ISO) typically specify the number of samples required.
• Data Provenance: Not explicitly stated as retrospective or prospective given this is laboratory testing of a physical product. The manufacturer is Guangzhou Fuzelong Hygiene Material Co., Ltd, China.

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

• Not applicable. This document describes laboratory performance testing of a physical medical device (a mask), not the evaluation of an AI algorithm's diagnostic performance requiring human expert ground truth. The "ground truth" here is the objective measurement of the mask's physical properties against defined standards.

4. Adjudication method for the test set:

• Not applicable. See point 3.

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 device.

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

• No. This is not an AI device.

7. The type of ground truth used:

• The "ground truth" for the mask's performance is based on objective measurements against pre-defined international and national standards (e.g., ASTM, EN, ISO, 16 CFR). For example, "Level 3 pass at ≥98%" for filtration efficiency is the acceptance criterion acting as the "ground truth."

8. The sample size for the training set:

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

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

• Not applicable. See point 8.

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