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The LoopView® is a sterile, single-use, flexible endoscope intended for endoscopic procedures and examination within the airways and tracheobronchial tree.

The endoscope is intended to provide visualization via MACROLUX™ video processor.

The endoscope is intended for use in a hospital environment. It is designed for use in adults. The ViewHub® is designed to display live imaging data from compatible MACROLUX™ endoscopes.

The Single-Use Diaital Flexible Bronchoscope System consists of LoopView® Single Bronchoscope (consists of a handle with control lever, endoscope cable and access port for accessories, and a flexible body portion) and ViewHub® Video Processor with its accessories including power cables. The LoopView® is provided sterile (sterilized by EO) and intended to be single-use. The ViewHub® is a reusable multi-patient use device.

The built-in LED at the Distal tip of the LoopView® Single Bronchoscope provides a light source, the lens module captures the light signal, then the CMOS module converts the light signal; the endoscope cable connects the LoopView® to the ViewHub®, which provides power and processes video signal from the endoscope; the control lever on the handle connected to the controllable portion by a wire rope controls the bending direction and angle of the controllable portion; the instrument channel delivers water and other instruments. Suctioning of saliva and mucus from airway is possible through the suction system.

The ViewHub® Video Processor is a video imaging system that receives video signals from the connected endoscope, controls the light at the endoscope tip and outputs this signal including a graphical user interface to a connected external video monitor.

The LoopView® Single-Use Digital Flexible Bronchoscope has the following physical and performance characteristics:

• Maneuverable tip controlled by the user
• Flexible insertion cord
• Camera and LED light source at the distal tip
• Sterilized by Ethylene Oxide
• For single-use

The ViewHub® Video Processor has the following physical and performance characteristics:

• Snapshot, white balance, zoom and HD video output

• supports HDMI video output formats

• Touch Panel

• Reusable

The provided text describes a 510(k) premarket notification for a medical device, the LoopView® Single-Use Digital Flexible Bronchoscope and ViewHub® Video Processor. It outlines the device's indications for use, technological characteristics, and non-clinical testing performed to establish substantial equivalence to a predicate device.

However, the document does not contain information about a study proving the device meets specific acceptance criteria in the context of AI/ML performance, human reader improvement with AI assistance, or related ground truth establishment. The testing described focuses on the device's physical and performance characteristics, biocompatibility, sterilization, electrical safety, and software verification/validation, typical for a Bronchoscope system.

Therefore, I cannot fulfill your request for:

• A table of acceptance criteria and reported device performance specific to an AI/ML component.
• Sample size used for the test set and data provenance for an AI/ML study.
• Number of experts and their qualifications for establishing ground truth for an AI/ML study.
• Adjudication method for an AI/ML test set.
• MRMC comparative effectiveness study results, effect size of human readers improving with AI vs. without AI assistance.
• Standalone (algorithm only) performance.
• Type of ground truth used (expert consensus, pathology, outcomes data) for AI/ML.
• Sample size for the training set for AI/ML.
• How the ground truth for the training set was established for AI/ML.

The document discusses "software verification and validation testing" but frames it as typically done for medical device software, which ensures functionality and safety, not necessarily AI/ML performance for diagnostic or assistive tasks.

In summary, the provided text details the FDA 510(k) clearance process for a bronchoscope system and its video processor, focusing on non-clinical testing for substantial equivalence. It does not include information on acceptance criteria or a study related to an AI/ML component's performance.

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