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The Medline Surgical Face Mask and Medline Procedural Face Mask are intended to be worn to protect both the patient and the healthcare worker from the 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. These masks are single use, disposable, non-sterile devices.

The Medline Surgical Face Mask and Medline Procedural Face Mask are single-use, disposable device, provided non-sterile. Depending on the configurations, the Medline Surgical Face Mask and Medline Procedural Face Mask are composed of three or four layers of nonwoven materials: an outer layer, middle filtration layer(s) and an inner facing layer. The outer/inner facing layers are constructed of non-woven fabric and the middle filtration layer(s) are constructed of melt blown non-woven fabric. Each mask contains tie strings or ear loops to secure the user's face and mouth, and come in a flat pleated style that includes a malleable nosepiece to provide a firm fit over the nose. The Medline Surgical Face Mask and Medline Procedural Face Mask may also come equipped with an antifog foam stripe, anti-glare stripe and/or a face shield to cover the upper part of the face. The Medline Surgical Face Mask and Medline Procedural Face Mask may also be provided in an ASTM Fluid level of Level 1, Level 2 or Level 3. The color of the facemasks will be available in white, yellow, blue, or pink stripes.

The provided document is a 510(k) Premarket Notification for a Medline Surgical Face Mask and Medline Procedural Face Mask. It primarily focuses on demonstrating substantial equivalence to a predicate device, which is different from an AI/ML medical device where the emphasis would be on the performance of an algorithm.

Therefore, the document does not contain the information requested regarding the acceptance criteria and study proving an AI/ML device meets those criteria. Specifically, it lacks data on:

• A table of acceptance criteria and reported device performance: This document specifies performance criteria and test results for physical properties of surgical masks (e.g., bacterial filtration efficiency, fluid resistance, flammability), not for the performance of an AI/ML algorithm.
• Sample size used for the test set and data provenance: No test set for an AI/ML algorithm is mentioned.
• Number of experts used to establish ground truth and their qualifications: Not applicable to a physical mask.
• Adjudication method for the test set: Not applicable.
• Multi-reader multi-case (MRMC) comparative effectiveness study: Not applicable.
• Standalone (algorithm only) performance: Not applicable.
• Type of ground truth used: Not applicable.
• Sample size for the training set: No training set for an AI/ML algorithm is mentioned.
• How ground truth for the training set was established: Not applicable.

Instead, the document details:

• Device Name: Medline Surgical Face Mask and Medline Procedural Face Mask
• Intended Use: To protect both the patient and healthcare worker from the transfer of microorganisms, body fluids, and particulate material; for use in infection control practices to reduce potential exposure to blood and body fluids. Single use, disposable, non-sterile.
• Predicate Device: Surgical Masks with Ear Loops or Ties, Level 1, Level 2, Level 3 (K202598)
• Non-Clinical Testing: Performance testing was completed based on standards like ISO 10993 (biocompatibility), ASTM F2101-19 (Bacterial filtration efficiency), ASTM F1862 (Resistance to penetration by synthetic blood), 16 CFR Part 1610 (Flammability), ASTM F2100 (Performance of Materials), EN 14683:2019 (Differential Pressure), and ASTM F2299 (Sub-micron particulate filtration efficiency).
• Clinical Testing: Not applicable (as stated in the document).

In summary, this document is for a medical device (surgical face mask) with physical performance requirements, not an AI/ML medical device, and therefore does not contain the specific information requested in the prompt about AI/ML device validation.

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