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The Infant Flow Plus System consisting of a Driver and Generator plus NCPAP Prongs and Masks, is intended for the provision of Bi-Level CPAP (SiPAP) to produce a sigh. The system is for use in Hospitals, Hospital-type facilities and intra-Hospital transport environments and is indicated for the treatment of Newborn and Infant patients.

The Infant Flow Plus System is a factory-installed modification to the Infant Flow Plus System. It uses the existing manually operated air / oxygen mixer and CPAP flow control. An ancillary manual flow control with electronic control solenoid valve allows timed delivery of augmented flow and pressure. The modification is housed in a robust enclosure that is designed to "piggy back" on to the existing Infant Flow Driver Unit.

The provided text describes a 510(k) premarket notification for the Infant Flow Plus System. This is a medical device and the performance data presented is related to its compliance with safety and electrical standards, not the clinical performance of an AI/ML algorithm.

Therefore, many of the requested categories in the prompt (e.g., acceptance criteria for an AI algorithm, sample size for test/training sets, number of experts for ground truth, adjudication methods, MRMC studies, standalone algorithm performance, type of ground truth for AI, etc.) are not applicable to this document. This document outlines the regulatory approval for a physical medical device.

However, I can extract the information relevant to the device's performance based on the standards it complies with.

Here's a summary of the available information:

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

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

• Not applicable. This document describes compliance with device safety and functional standards, not a clinical study involving a test set of patient data.

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

• Not applicable. Ground truth in the context of AI/ML is not relevant here. The "ground truth" for these standards would be the specifications and requirements defined by the standards themselves, validated through engineering tests.

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

• Not applicable. No adjudication method for a test set of patient data is mentioned as it's not a clinical study. Compliance with standards is typically verified through documented testing and review processes by qualified engineers and regulatory bodies.

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 device is an Infant Flow Plus System, a bi-level CPAP system, not an AI diagnostic tool. No MRMC study or AI assistance is mentioned.

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

• Not applicable. This refers to an AI/ML algorithm's performance. The Infant Flow Plus System is a physical medical device.

7. The type of ground truth used:

• Not applicable in the AI/ML sense. For the device itself, the "ground truth" for its performance is its adherence to the technical specifications and safety requirements outlined in the cited IEC and UL standards.

8. The sample size for the training set:

• Not applicable. There is no AI/ML training set mentioned in this document.

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

• Not applicable. There is no AI/ML training set mentioned in this document.

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