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The Nio 5MP Medical Flat Panel Display System is intended to be used in displaying and viewing digital images, excluding digital mammography, for review by trained medical practitioners.

The Nio 5MP Medical Flat Panel Display System is intended to be used as a tool in displaying and viewing digital images (excluding digital mammography) for review and analysis by trained medical practitioners.

The Nio 5MP device is a digital image display system.

The Nio 5MP device consists of components to provide high resolution visualization of digital images.

The provided text is a 510(k) summary for a medical flat panel display system (Nio 5MP) and its FDA clearance letter. It does not contain information about acceptance criteria or a study proving that the device meets those criteria, as typically understood for AI/algorithm-based medical devices.

Instead, this document focuses on establishing substantial equivalence for a hardware display system based on its intended use and technological characteristics compared to a predicate device.

Therefore, I cannot fulfill your request for the specific information regarding acceptance criteria and a study that proves the device meets those criteria for this particular submission. The device described is a display system, not an AI/algorithm producing diagnostic outputs for which performance metrics like sensitivity, specificity, or AUC would be established through clinical studies.

The information provided confirms:

• Device Name: Nio 5MP Medical Flat Panel Display System
• Intended Use: "displaying and viewing digital images, excluding digital mammography, for review by trained medical practitioners."
• Classification: Image processing system, Class II, Product Code 90 LLZ.
• Predicate Device: Nio 5MP Medical Grayscale Display System (K040040)

Without a study described in the provided text, I cannot provide details on the following:

1. A table of acceptance criteria and the reported device performance: Not applicable.
2. Sample sized used for the test set and the data provenance: Not applicable.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable.
4. Adjudication method for the test set: Not applicable.
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.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not applicable.
7. The type of ground truth used: Not applicable.
8. The sample size for the training set: Not applicable.
9. How the ground truth for the training set was established: Not applicable.

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