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Exact Medical Manufacturing Surgical Gown with AAMI Liquid Barrier Level IV are sterile or nonsterile single use devices that are intended to be worn by operating room personnel during surgical procedures to protect both the surgical patient and the operating room personnel from transfer of microorganisms, body fluids, and particulate material. Sterile surgical gowns are to be sold directly to users after E.O sterlization and validated to ISO 11135-1:2007.

The Exact Medical Manufacturing Surgical Gowns with AAMI Level IV Liquid Barner are also sold as bulk non-sterile, single use items, to repackager/relabeler establishments for further packaging and ethylene oxide sterilization according to ISO 11135-1:2007

Exact Medical Manufacturing Surgical Gown with AAMI Liquid Barrier Level IV are sterile or non-sterile single use devices that are intended to be worn by operating room personnel during surgical procedures to protect both the surgical patient and the operating room personnel from transfer of microorganisms, body fluids, and particulate material.
Exact Medical Manufacturing Surgical Gown with AAMI Liquid Barrier Level IV is comprised of a 3 ply laminate non woven material - outer layers are nonwoven fabric - inner layer AAMI PB:70 Level 4 capable film. The gowns consist of 100% polyester cuffs sewn to the end of the sleeves using nylon thread. The gowns have a manual closure system.

The provided text describes the 510(k) summary for the Exact Medical Manufacturing Surgical Gown with AAMI Liquid Barrier Level IV. This document focuses on the regulatory submission and does NOT involve an AI/ML algorithm or a study with human readers, deep learning, or image analysis. Therefore, many of the requested categories are not applicable.

Here's an analysis of the provided information:

Acceptance Criteria and Reported Device Performance

The device is a surgical gown, and its performance is evaluated against established standards for medical textiles, particularly AAMI PB:70 Level 4 for barrier properties.

Study Information (Not Applicable for this Device Type)

The provided document describes a device for regulatory approval (510(k) submission) for a physical medical device (surgical gown), not a diagnostic AI/ML algorithm or software. Therefore, the following points are not applicable.

1. Sample size used for the test set and the data provenance: Not applicable. Tests are conducted on physical samples of the gown material, not a "test set" of data or patient cases.
2. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable. Material testing standards define performance, not expert ground truth on cases.
3. Adjudication method (e.g., 2+1, 3+1, none) for the test set: Not applicable.
4. 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.
5. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not applicable.
6. The type of ground truth used (expert consensus, pathology, outcomes data, etc.): Not applicable. "Ground truth" here refers to the measured physical properties of the material against established international standards.
7. The sample size for the training set: Not applicable. There is no training set for a physical device like a surgical gown.
8. How the ground truth for the training set was established: Not applicable.

Explanation of "Not Applicable" for AI/ML-specific questions:

The 510(k) summary is for a physical medical product (surgical gown), not a software or AI/ML algorithm. The performance evaluation revolves around bench testing of the physical material's properties (e.g., barrier effectiveness, strength, biocompatibility) against established industry standards (like AAMI PB:70 Level 4 and ISO 10993). Concepts such as "test set," "training set," "data provenance," "expert ground truth," "adjudication," "multi-reader multi-case studies," or "human-in-the-loop performance" are specific to the validation of diagnostic algorithms or AI-powered systems, which are not relevant to this product.

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