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The FiberFlo™ series of Hollow Fiber Capsule Water Filters is intended to filter bacteria, endotoxin and particulate matter from water used for hemodialysis applications.

The FiberFlo™ Hollow Fiber Capsule Water Filters consist of encapsulated microporous polysulfone membrane in a polycarbonate housing with multiple endcap connections to filter endotoxins, bacteria and particulates from water.

The provided document is a 510(k) premarket notification for a medical device (FiberFlo™ Hollow Fiber Capsule Water Filters) and does not describe a study involving AI or machine learning. Therefore, most of the requested information regarding acceptance criteria, device performance, and study design relevant to AI models cannot be extracted.

However, I can provide the limited information available regarding the device's performance testing and general characteristics.

Information Extracted from the Document (Non-AI Device):

The document describes a conventional water filter, not an AI-powered device. Therefore, the questions related to AI acceptance criteria, sample sizes for AI training/test sets, ground truth establishment by experts, and MRMC studies are not applicable.

1. A table of acceptance criteria and the reported device performance:

The document mentions performance testing but does not explicitly state numerical acceptance criteria or detailed quantitative results for each test. It broadly states that the testing was "to support substantial equivalence."

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

Not applicable, as this is a physical device, not an AI model evaluated on a data set. The performance testing would involve physical units of the filter.

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):

Not applicable. Ground truth for a physical filter's performance is established through laboratory measurements and established testing protocols, not expert consensus on data.

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

Not applicable.

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.

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

Not applicable.

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

For this physical device, the "ground truth" would be objective measurements from laboratory tests according to recognized standards (e.g., bacterial retention challenge tests, endotoxin assays, flow rate measurements).

8. The sample size for the training set:

Not applicable.

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

Not applicable.

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