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The Nio Color 3MP LED Medical Flat Panel Display System is intended to be used for displaying and viewing digital images (excluding digital mammography) for review and analysis by trained medical practitioners.

The display may be used in dental applications.

The MDNC-3421 is a derivative of the MDNC-3321. The modifications are:
✓ PLD panel instead of NLT panel
✓ Change in packaging (smaller size)
✓ Updated firmware
✓ Change in type of material from steel to aluminum (inside metal housing)
✓ For the dental radiology market, this display will be marketed with the screen in landscape orientation

Here's an analysis of the acceptance criteria and study information based on the provided document:

This document is a 510(k) premarket notification for a medical display system, which often focuses on demonstrating substantial equivalence to a predicate device rather than extensive clinical studies for novel technologies.

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly state "acceptance criteria" in a quantitative, pass/fail format typical of AI/CADe devices. Instead, it demonstrates substantial equivalence by comparing the new device (MDNC-3421) to a predicate device (MDNC-3321) based on technical specifications and performance testing. The "reported device performance" is implicitly shown by the new device meeting or exceeding the specifications of the predicate device and showing no new safety or performance issues.

2. Sample size used for the test set and the data provenance

The document primarily describes bench testing and, for one specific aspect, mentions a "Clinical study."

• Bench Tests (for hardware/firmware changes, safety, and EMC): No specific sample sizes (e.g., number of displays tested) are provided for tests like PPVR, Environmental tests, Firmware tests, Electrical Safety (IEC 60601-1), and EMC (IEC 60601-1-2). These are typically engineering validation tests. The provenance is internal to the manufacturer's testing process.
• Clinical Study (for landscape/portrait orientation marketing): A "Clinical study" is mentioned for validating the marketing of the display in landscape/portrait orientation. However, no details are provided regarding the sample size, data provenance (e.g., country of origin, retrospective/prospective nature), or the methodology of this study. This suggests it was likely a usability or preference study relevant to display orientation, rather than a clinical trial assessing diagnostic accuracy.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts

This information is not provided in the document. Given that the core of the submission relies on demonstrating substantial equivalence through technical specifications and bench testing, rather than a diagnostic performance study, the establishment of "ground truth" by medical experts is not a primary focus here. The clinical study mentioned is too briefly described to extract this information.

4. Adjudication method for the test set

This information is not provided in the document. As noted above, the predominant testing described is bench testing, where adjudication by medical experts isn't applicable in the same way as in a diagnostic study.

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

No, a multi-reader multi-case (MRMC) comparative effectiveness study was not described or implied in this document. This device is a medical display system, not an AI/CADe diagnostic algorithm. Therefore, the concept of "how much human readers improve with AI vs without AI assistance" is not relevant to this submission.

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

No, a standalone performance study of an algorithm was not done. This device is a display monitor, not an algorithm.

7. The type of ground truth used

For the bench tests, the "ground truth" consists of engineering specifications, industry standards (e.g., DICOM, IEC 60601-1), and established performance metrics (e.g., luminance, contrast ratio, response time). These are not expert consensus, pathology, or outcomes data. For the mentioned "clinical study," the type of ground truth is not specified due to the lack of detail.

8. The sample size for the training set

This information is not applicable as this device is a medical display system, not a machine learning or AI algorithm that requires a training set.

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

This information is not applicable for the same reason as above.

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