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The IntubaidFlex" is intended for use as an aid in the placement of an Endotracheal Tube (ETT) directly or through an Intubating Laryngeal Mask Airway (LMA) during non difficult and difficult intubation procedures. The IntubaidFlex achieves its purpose by providing the user with a visual confirmation of where the tip of the device is in the human anatomy. The flexible tip of the IntubaidFlex allows the user to guide the ETT in the desired direction.

The IntubaidFlex" is a simple, disposable, single-patient use, sterile, handheld, portable stylet with a built in camera, that fits within an Endotracheal tube (ETT) directly or through an Intubating Laryngeal Mask Airway(LMA) and provides for video-assisted visualization of the laryngeal inlet. The IntubaidFlex" can plug into any TV monitor, hand held monitor or PC (via USB) for live video visualization.

The provided text describes a medical device, the IntubaidFlex™, and its substantial equivalence to a predicate device for 510(k) clearance. However, it does not contain information about acceptance criteria, reported device performance in those criteria, or a study that specifically proves the device meets those criteria, particularly in the context of AI/ML performance.

The submission is for a medical device (a stylet/videoscope) and not an AI/ML powered device. The document primarily focuses on demonstrating substantial equivalence to a predicate device through biocompatibility, electrical safety, electromagnetic compatibility, and bench testing, as well as outlining its intended use.

Therefore, most of the requested information regarding AI/ML-specific acceptance criteria and studies cannot be extracted from this document.

Here's what can be answered based on the provided text:

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

Regarding the other requested information (2-9):

The provided text does not include the following information, as it pertains to a traditional medical device submission and not an AI/ML driven one:

• Sample size used for the test set and the data provenance: Not applicable to this type of device submission. The "test set" here refers to physical bench tests rather than data for an algorithm.
• Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable. Ground truth for a physical device's performance in these categories (biocompatibility, electrical safety, mechanical strength) is established through standardized laboratory testing, not expert consensus on data.
• Adjudication method for the test set: Not applicable.
• 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 is not an AI-powered device.
• If a standalone (i.e. algorithm only without human-in-the loop performance) was done: Not applicable. This is not an AI-powered device.
• The type of ground truth used (expert consensus, pathology, outcomes data, etc): Not applicable in the context of an AI/ML algorithm. Ground truth for this device's performance relies on physical and electrical measurements against established standards.
• The sample size for the training set: Not applicable. This is not an AI-powered device.
• How the ground truth for the training set was established: Not applicable. This is not an AI-powered device.

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