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RadiForce GX220 and RadiForce GS220 are intended to be used in displaying for diagnosis in CT, DSA or MRI etc., except for a digital mammography system.

RadiForce GX220 and Radiforce GS220 are a 54cm (21,3") Monochrome LCD display for medical image viewing, RadiForce GX220 and RadiForce GS220 display high-definition medical imaging. The model difference between GX220 and GS220 are the built-in swing calibration sensor and the protection panel equipped with GX220 as standard feature.

This document is a 510(k) summary for the EIZO NANAO Monochrome LCD Monitors, RadiForce GX220 and RadiForce GS220, from 2007. It outlines the device's classification, intended use, and technological characteristics compared to a predicate device. However, it does not include detailed information regarding acceptance criteria or a study proving the device meets specific performance metrics in the way a modern AI/ML medical device submission would.

This document describes a medical imaging display monitor, not an AI/ML device. Therefore, the questions related to AI/ML specific criteria (such as ground truth, training sets, MRMC studies, standalone performance with AI, etc.) are not applicable here.

Here's the information that can be extracted from the provided text, primarily regarding the device itself and its comparison to a predicate device for substantial equivalence:

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

The document does not explicitly state "acceptance criteria" in a quantitative performance metric sense for image display quality. Instead, it focuses on substantial equivalence to a predicate device (RadiForce G22, K041597). The "performance" is implicitly tied to meeting the functional requirements expected of a medical display for diagnosis in CT, DSA, or MRI.

The statement: "Any difference between both devices not affects safety or efficacy" is the primary "acceptance criterion" met through comparison to the predicate device. The changes (smaller grayscale tones, larger panel, DUE, sensor, protection panel) are presented as not negatively impacting safety or efficacy, thus demonstrating substantial equivalence.

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

Not applicable. This is a display monitor, not a data-driven diagnostic device. There is no "test set" of medical images or patient data to evaluate its diagnostic performance in the way an AI/ML algorithm would be tested. The evaluation is on display characteristics and functionality.

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)

Not applicable. See point 2.

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

Not applicable. See point 2.

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. This is not an AI-assisted device.

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

Not applicable. This is a display monitor, not an algorithm.

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

Not applicable. See point 2.

8. The sample size for the training set

Not applicable. This is not an AI/ML device.

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

Not applicable. This is not an AI/ML device.

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