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The Raider guidewire is intended for use in percutaneous procedures to introduce and position catheters and other interventional devices within the coronary and peripheral vasculature.

The Raider guidewire is a stainless steel core guidewire with a maximum outer diameter of 0.014″ and a straight, shapeable tip. It is available in 190 cm and 300 cm length is compatible with a guidewire extension. The distal portion of the guidewire includes a radiopaque coil and is covered with a polymer jacket and hydrophilic coating. The proximal portion has a PTFE coating.

The provided text is a 510(k) summary for the Raider Guidewire. It outlines the device's indications, technological characteristics, and testing performed to demonstrate substantial equivalence to a predicate device. However, this document does not contain the kind of detailed information about acceptance criteria or a study design (like sample size for test sets, data provenance, expert demographics, adjudication methods, MRMC studies, or standalone algorithm performance) that you would typically find for an AI/ML medical device.

The Raider Guidewire is a physical medical device (a catheter guide wire), not an AI/ML software device. Therefore, the questions posed in the prompt, which are highly specific to the evaluation of AI/ML diagnostic or predictive algorithms, are not applicable to the information provided in this 510(k) summary.

The document discusses "acceptance criteria" in a general sense through performance testing for mechanical properties and biocompatibility.

Here's the information that can be extracted or inferred from the provided text, while acknowledging that many of your questions cannot be answered because they pertain to a different type of device:

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

The document doesn't provide specific numerical acceptance criteria for each test (e.g., "Tensile strength > X Newtons"). Instead, it states that "Device samples passed the following biocompatibility tests" and "The device design has been verified through the following tests." This implies that predefined acceptance criteria were met, but the specific values are not detailed.

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

This information is not provided in the document. For mechanical and biocompatibility testing of a physical device, samples are typically manufactured batches tested in a lab setting, not "test sets" in the AI/ML sense. Data provenance (country of origin, retrospective/prospective) is not relevant for this type of testing.

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):

This information is not applicable/provided. "Ground truth" in the context of this device refers to objective measurements derived from physical and chemical tests, not expert interpretation of data.

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

This information is not applicable/provided. Adjudication methods are relevant for human interpretation tasks, not for the objective testing of physical device properties.

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:

This information is not applicable/provided. MRMC studies and AI assistance are relevant for AI/ML diagnostic devices, not for a guidewire.

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

This information is not applicable/provided. This refers to AI algorithm performance, which is not relevant for this physical device.

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

The "ground truth" for this device's performance is based on objective measurements from standard mechanical, material, and biological tests (e.g., tensile strength testing, chemical assays for biocompatibility, dimensional measurements). It is not based on expert consensus, pathology, or outcomes data in the way an AI/ML diagnostic system would be evaluated.

8. The sample size for the training set:

This information is not applicable/provided. Training sets are for AI/ML models. This device is a physical product.

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

This information is not applicable/provided. (See #8).

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