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The device is intended to be used as a tool in displaying and viewing digital images, including digital mammography system for view and analyses by trained medical practitioner.

The MMD-5201M LCD monitors are displays for medical use. MMD-5210M provides 5 mega pixel resolution and 766 grayscales per pixel display. The display device is complied with the standard ISO13406-2 to conform to the requirement of the mammography display system.

The provided text describes a 510(k) summary for the PACSmate MMD-5201M monitor. This document focuses on the regulatory clearance of a medical display device, not an AI or diagnostic algorithm, therefore, many of the requested criteria related to AI/algorithm performance and clinical studies are not applicable.

Here's an analysis of the available information:

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

The document does not explicitly state "acceptance criteria" in a numerical table form for performance. Instead, it indicates compliance with standards and equivalence to a predicate device.

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

This information is not provided in the document. The performance testing "demonstrated that the device meets its intended use specifications," but details about the methodology, sample size of images or cases tested, or data provenance are absent. As this is a display monitor, the "test set" would likely refer to images displayed on the monitor, but no specifics are given.

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)

This information is not provided and is largely not applicable for a medical display device. The device itself is not making a diagnostic judgment, so there is no "ground truth" in the sense of expert consensus on disease presence/absence to be established for the display's own performance. The document states the device is for "viewing and analyses by trained medical practitioner," implying the target user, but not for defining ground truth for the display's testing.

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

This information is not provided and is not applicable for a medical display device. Adjudication methods are typically used in studies where human readers are interpreting images and their agreement is being assessed against a ground truth.

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

There is no indication that an MRMC comparative effectiveness study was done. This type of study is relevant for AI or CAD (Computer-Aided Detection/Diagnosis) systems, not for a passive display monitor. The device itself is a display, not an AI or CAD tool.

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

This is not applicable. The device is a display monitor, not an algorithm. Its function is to render images for human interpretation, not to provide an automated diagnostic output.

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

This is not applicable for a medical display monitor in the context of its performance validation. The "ground truth" for a display would refer to the fidelity of the image presentation, adherence to display standards, and visual quality, not diagnostic accuracy based on pathology or outcomes.

8. The sample size for the training set

This is not applicable. The PACSmate MMD-5201M monitor is a hardware device. It does not utilize a "training set" in the context of machine learning.

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

This is not applicable for the same reason as point 8.

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PACSmate MMD=4300C/4300CX is intended to be used in displaying and viewing digital images for diagnosis of X-ray or MRI, etc. by trained medical practitioners. PACSmate MMD-4300C/4300CX does not support the display of mammography images for diagnosis.

The PACSmate MMD-4300C/4300CX is a 30" monochrome/color LCD display for medical image viewing.4 Mega pixel medical grade LCD monitor with high resolutions.

The provided document describes a 510(k) summary for the PACSmate MMD-4300C/4300CX medical display. This device is a monitor used for displaying medical images, not an AI-powered diagnostic tool. Therefore, many of the requested categories related to AI performance, such as sample sizes for test sets, expert adjudication, MRMC studies, standalone performance, and ground truth establishment for AI models, are not applicable to this submission.

The "study that proves the device meets the acceptance criteria" refers to bench testing demonstrating the device's conformance to applicable standards and its substantial equivalence to a predicate device.

1. Table of Acceptance Criteria and Reported Device Performance

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 medical display device, not an AI diagnostic algorithm that processes image data from a test set. The performance evaluation is based on engineering specifications and adherence to standards, not analysis of clinical images.

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. Ground truth for clinical images is not established for this type of device. The assessment is based on technical specifications and safety standards.

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

Not applicable. Adjudication methods are relevant for evaluating diagnostic accuracy using human readers or AI algorithms on clinical cases, which is not the purpose of this device's submission.

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. An MRMC study was not done as this is a medical display device and does not involve AI assistance for human readers in a diagnostic capacity.

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

No. This device is a display monitor and does not involve any standalone algorithm performance.

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

Not applicable. The "ground truth" for this device's performance evaluation is based on engineering specifications, recognized industry standards (IEC 60601-1, IEC 60601-1-2), and comparison to a legally marketed predicate device's characteristics.

8. The sample size for the training set

Not applicable. This device does not use a training set as it is not an AI algorithm.

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

Not applicable. This device does not use a training set.

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The device is intended to be used to as a tool in displaying and viewing digital images view and analyses by trained medical practitioner. The device is not specified for digital mammography system.

The MMD-3213M LCD monitors are displays for medical image viewing. MMD-3213M provides 3 mega pixel resolution. The PACSmate MMD-3213M is a high performance, 3 Megapixel medical grade monochrome LCD monitors designed for exacting needs for diagnostics professionals that provide clear and sharp images with resolutions of up to 2048 x 1536 pixels, 600 cd/m2 brightness and 700:1 contrast ratio, making it ideal for diagnosing detailed medical graphics. Also uses a DVI digital interface offering compatibility with the latest digital standards.

The provided text describes a 510(k) premarket notification for a medical display device, the PACSmate MMD-3213M monitor. However, it does not contain the detailed performance study information, acceptance criteria, or ground truth establishment relevant to the questions asked.

The document primarily focuses on demonstrating substantial equivalence to a predicate device (EIZO RadiForce GS320) based on intended use, construction, function, safety, operating environmental conditions, and effectiveness. It mentions "Performance Testing" but only states: "The performance test results for the PACSmate LCD monitor demonstrated that the device meets its intended use specifications and therefore meets the requirements necessary for its intended use as a displayer for medical image." It does not provide the specific acceptance criteria or the actual results of these performance tests.

Therefore, I cannot populate the table or answer most of your specific questions based on the provided text.

Here's what can be extracted and what cannot:

1. Table of acceptance criteria and the reported device performance:

• Cannot be provided from the text. The document states "device meets its intended use specifications" but does not define these specifications or provide quantitative performance metrics.

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

• Cannot be provided from the text. There is no mention of a "test set" in the context of image analysis or diagnostic performance. The performance testing likely refers to technical specifications of the monitor itself (e.g., brightness, contrast, resolution) rather than clinical image interpretation studies.

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

• Cannot be provided from the text. No ground truth establishment is described, as the device is a display monitor, not an AI diagnostic algorithm.

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

• Cannot be provided from the text. Not applicable for a display monitor's performance testing described here.

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:

• Cannot be provided from the text. Not applicable, as this is a medical display, not an AI-powered diagnostic tool. The document focuses on the monitor's technical compliance and substantial equivalence.

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

• Cannot be provided from the text. Not applicable; it's a monitor.

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

• Cannot be provided from the text. Not applicable.

8. The sample size for the training set:

• Cannot be provided from the text. Not applicable; this is a display monitor, not an AI algorithm.

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

• Cannot be provided from the text. Not applicable.

In summary, the provided document describes the regulatory approval of a medical display monitor based on its technical specifications and substantial equivalence to a predicate device. It does not include information about clinical studies, diagnostic performance, expert review, or ground truth establishment, which are typical for AI-based diagnostic devices.

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