Search Results

Ask a specific question about this device

Ask a specific question about this device

Ask a specific question about this device

Ask a specific question about this device

Ask a specific question about this device

Ask a specific question about this device

Ask a specific question about this device

The Barco MeDis 5MP 5 MegaPixel Medical Diagnostic Display System is intended to be used in displaying and viewing digital images for review and analysis by trained medical practitioners.

The MeDis 5MP device is a digital image display system. The Barco MeDis 5MP 5 MegaPixel Medical Diagnostic Display System device consists of components to provide high resolution visualization of digital images.

This submission pertains to the Barco MeDis 5MP 5 MegaPixel Medical Diagnostic Display System.

It's crucial to understand that this 510(k) summary is for a medical display system, not an AI algorithm or a diagnostic software. Therefore, the "acceptance criteria" and "study" described are focused on the display's performance characteristics for medical image viewing, rather than the diagnostic accuracy of an AI.

Given that context, here's an analysis of the provided information:

1. Table of Acceptance Criteria and Reported Device Performance

The provided document does not explicitly state specific, quantifiable acceptance criteria or a dedicated study comparing the device against such criteria. This is common for display devices in this regulatory era, where the focus is on demonstrating substantial equivalence to existing predicate devices meeting general performance expectations for medical imaging.

Instead, the submission implies acceptance based on the device's technical specifications and its ability to meet the general requirements for "displaying and viewing digital images for review and analysis by trained medical practitioners." The comparison is primarily against predicate devices with similar intended uses and technological characteristics.

Therefore, the "acceptance criteria" can be inferred from the device's description and the general requirements for medical displays at the time. The "reported device performance" is essentially the specifications of the MeDis 5MP.

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

N/A. This device is a display system, not an AI algorithm or a diagnostic software that would process a "test set" of medical data. Its performance is assessed through its hardware specifications and compliance with general display standards, often demonstrated through internal testing and comparisons to predicate devices. There is no mention of a "test set" of images for diagnostic performance evaluation in this 510(k) summary.

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

N/A. As a display system, there is no "ground truth" to be established by experts related to the device's diagnostic performance. The ground truth concept is relevant for AI algorithms or diagnostic tools that interpret medical images.

4. Adjudication method for the test set

N/A. No test set or expert adjudication is described for a display system.

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 MRMC comparative effectiveness study is designed to evaluate the impact of a diagnostic tool (like AI) on human reader performance. This submission is for a medical display system, not a diagnostic AI tool, so such a study would not be applicable or expected.

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

No. This is a hardware display system, not an algorithm. Standalone performance is relevant for software algorithms that operate independently.

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

N/A. As explained, the concept of "ground truth" for diagnostic accuracy is not relevant to a medical display system itself. The device is evaluated on its ability to accurately render images, not to interpret or diagnose them.

8. The sample size for the training set

N/A. As a hardware medical display system, there is no "training set" in the context of machine learning or AI.

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

N/A. This question is not applicable for a medical display system.

Ask a specific question about this device

The Barco MGD 521 5 MegaPixel Diagnostic Display is intended to be used in displaying and viewing digital images for review and analysis by trained medical practitioners.

The MGD 521 device is a diagnostic display. The Barco MGD 521 is a electronic resolution monitor with high resolution capabilities for evaluation of high medical images.

This is a medical device, a Monitor/Display, not an AI/ML device, so many of the requested fields are not applicable.

1. Table of Acceptance Criteria and Reported Device Performance

2. Sample Size for Test Set and Data Provenance

Not applicable. This is a hardware display device, not an AI/ML diagnostic tool that processes a "test set" of medical images.

3. Number of Experts Used to Establish Ground Truth and Qualifications

Not applicable. The device's performance is based on its technical specifications for displaying images, not on expert interpretations of data it processes.

4. Adjudication Method

Not applicable.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

Not applicable. This device is a display monitor, not an AI system designed to assist human readers.

6. Standalone (Algorithm Only) Performance Study

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

7. Type of Ground Truth Used

Not applicable. The "ground truth" for a display device would primarily relate to its technical specifications (e.g., resolution, brightness, contrast, color accuracy) and its ability to accurately render images as intended by the source, rather than a clinical ground truth like pathology or outcomes data.

8. Sample Size for Training Set

Not applicable. This is a hardware device; it does not have a "training set" in the context of machine learning.

9. How Ground Truth for Training Set Was Established

Not applicable.

Ask a specific question about this device

The Barco MWD 321 device is intended to be used in displaying and viewing digital images for and analysis review by trained medical practitioners.
The Barco MWD 321 Medical Workstation is intended to be used in displaying and viewing digital images for review and analysis by trained medical practitioners.

The MWD 321 device is a workstation display.
The Barco MWD 321 is a monitor high resolution with electronic capabilities for evaluation of high resolution medical images.

This is a medical display workstation, which is a hardware device. The provided text doesn't contain a study that proves the device meets acceptance criteria in the way one would evaluate an AI/software medical device (e.g., diagnostic accuracy, sensitivity, specificity).

The "study" in this context refers to the substantial equivalence comparison made by FDA to legally marketed predicate devices. The acceptance criteria for such a device are primarily based on its technical specifications and performance characteristics being comparable to, and not raising new questions of safety or effectiveness compared to, predicate devices.

Here's the breakdown based on the information provided:

Acceptance Criteria and Device Performance

Since this is a hardware device (medical display workstation), the acceptance criteria are not typically presented as performance metrics like sensitivity/specificity for a diagnostic algorithm. Instead, they relate to technical specifications that ensure it functions as intended for displaying medical images for review and analysis. The "performance" being evaluated is its ability to perform the intended function comparably to predicate devices.

Study Information (as applicable for a hardware device submission)

1. Sample size used for the test set and the data provenance: Not applicable in the context of an AI/software diagnostic study. For a hardware device like a display, "testing" would involve engineering validation against specifications, not a diagnostic performance study on a test set of medical images in the same way as an AI algorithm. The FDA's substantial equivalence determination relies on comparing the device to existing predicate devices.

2. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable. Ground truth as in diagnostic accuracy is not established for a display monitor.

3. Adjudication method (e.g. 2+1, 3+1, none) for the test set: Not applicable.

4. 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 a display monitor, not an AI-assisted diagnostic tool.

5. If a standalone (i.e. algorithm only, without human-in-the-loop performance) was done: Not applicable. This is a hardware device.

6. The type of ground truth used (expert consensus, pathology, outcomes data, etc.): Not applicable. The "ground truth" for a display workstation is its technical specifications and its ability to accurately render images, not a diagnostic ground truth for medical conditions.

7. The sample size for the training set: Not applicable. Hardware devices are not "trained" with data in the same way AI algorithms are.

8. How the ground truth for the training set was established: Not applicable.

Ask a specific question about this device