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The Dillard Airway Dilatation System is intended to dilute strictures of the airway trees.

The Dillard Airway Dilatation System includes a balloon catheter whose working length is 25cm or 100cm, and is available in balloon diameters from 5mm to 12mm and balloon lengths of 20mm and 40mm. The balloon component of the catheter has radiopaque markers to assist with radiographic positioning (as applicable). The proximal end of the device is a common catheter design consisting of a plastic hub and strain relief. The hub is used to inflate the balloon and the luer connector integrated into the hub is compatible with standard inflation devices. A second lumen within the catheter, intended for guidewire use, extends through the central lumen back to the proximal hub and through the distal tip. All catheters and accessories are supplied sterile and intended for single use.

The provided text describes the Dillard Airway Dilatation System (K153484) and its claim of substantial equivalence to a predicate device. However, it does not contain information related to an AI/ML-driven device or study results with acceptance criteria.

The document is a 510(k) premarket notification for a medical device (dilatation catheter) and focuses on demonstrating substantial equivalence to a legally marketed predicate device through physical descriptions, indications for use, comparison of characteristics, and traditional performance testing.

Therefore, I cannot fulfill your request for the following reasons derived from the text:

1. No AI/ML Device: The device described, the Dillard Airway Dilatation System, is a physical medical instrument (a balloon catheter) used for dilating airway strictures. It is not an AI/ML software or system.
2. No Acceptance Criteria for AI/ML Performance: Since it's a physical device, the "acceptance criteria" and "reported device performance" are related to mechanical and biocompatibility tests (e.g., dimensional specifications, joint separation strength, balloon burst pressure, inflation/deflation times, cycle fatigue, biocompatibility), not AI/ML metrics like sensitivity, specificity, or AUC.
3. No Human Reader Study: As it's not an AI/ML device, there are no mentions of sample sizes for test sets, data provenance, expert ground truth establishment, adjudication methods, or MRMC studies.
4. No Standalone Algorithm Performance: The concept of "standalone performance" for an algorithm is not applicable to a physical medical device.
5. No Ground Truth for Training Set: There is no training set mentioned, as it's not a machine learning model.

The document solely focuses on demonstrating substantial equivalence of a physical medical device to a predicate device through conventional engineering and biological testing.

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