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CL-S301 is intended to be used in displaying and viewing medical images for diagnosis by trained medical practitioners or certified personnel. It is not meant to be used in digital mammography.

21.3 inch Color LCD Monitor
1536 x 2048 (portrait)
High-luminance color LCD panel, which has wide view angle, is used for this product. It is designed for medical image display. Luminance stabilization function composed with luminance sensor and luminance control circuit always observes the luminance and makes it stable. Images are faithfully displayed along grayscale characteristics (DICOM GSDF) based on the calibrated data stored to the lookup table of the monitor. Luminance and the color mura correction functions will help achieve uniformity on the whole screen.

The provided FDA 510(k) summary is for a medical monitor (3MP Color LCD Monitor CL-S301), not an AI device. Therefore, much of the requested information regarding AI device acceptance criteria, study design, and performance metrics (e.g., sample sizes for test/training sets, ground truth establishment, expert adjudication, MRMC studies) is not applicable or cannot be extracted from this document, as it pertains to the performance evaluation of a display hardware.

However, I can extract the acceptance criteria and performance data related to the physical characteristics of the monitor, as well as general information about its intended use and comparison to a predicate device.

Here's the available information based on the provided text:

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

The document presents performance "test items in the guidance" which serve as acceptance criteria for a medical display monitor. The "test method(s)" column describes how these criteria are verified. The conclusion states that "The results of the performance testing and the verification demonstrate that the subject device is substantially equivalent to the currently marketed predicate device." This implicitly means the device met the acceptance criteria for each test.

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

This information is not applicable to a physical display device. The tests are performed on the device itself, not on
a "data set" in the context of an AI algorithm. The device manufacturer is JVCKENWOOD Corporation, located in Japan.

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 is not applicable. The "ground truth" for a monitor's performance is based on physical measurements and adherence to technical standards (e.g., ISO, IDMS, AAPM-TG directives), not expert interpretation of medical images.

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

This is not applicable. Adjudication methods are relevant for evaluating expert performance on diagnostic tasks, not for physical device testing.

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

This is not applicable. An MRMC study is used to evaluate the diagnostic performance of a system (often AI-assisted) with human readers. This document describes a monitor, which is a display hardware, not a diagnostic AI system.

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

This is not applicable as the device is a display monitor, not an algorithm.

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

The "ground truth" for the monitor's performance is defined by adherence to established technical standards and measurement protocols (e.g., ISO 13406-2, IDMS 1.03, AAPM-TG18/196, IEC 62563-1).

8. The sample size for the training set

This is not applicable. The device is a physical monitor, not an AI algorithm that requires a training set.

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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CL-R813 is intended to be used in displaying and viewing medical images for diagnosis by trained medical practitioners or certified personnel.

It is not meant to be used in digital mammography.

32-inch 8MP Color LCD Monitor CL-R813, 3840 x 2160 (landscape)

• Color LCD panel, which has wide view angle, is used for this product. It is designed for medical image display.
• Luminance stabilization function composed with luminance sensor and luminance control circuit always observes the luminance and makes it stable.
• Images are faithfully displayed along grayscale characteristics (DICOM GSDF) based on the calibrated data stored to the lookup table of the monitor.
• Luminance mura correction functions will help achieve uniformity on the whole screen.

The provided text describes a 510(k) summary for the JVCKENWOOD 8MP Color LCD Monitor CL-R813. It is a submission for a display device, not an AI/ML medical device. Therefore, many of the requested categories related to AI/ML device studies (such as sample sizes for test and training sets, expert qualifications, adjudication methods, MRMC studies, standalone performance, and specific ground truth types like pathology or outcomes data) are not applicable to this document.

However, I can extract information regarding the device's technical performance and the tests conducted to demonstrate its characteristics.

Here's a summary of the available information:

1. Table of Acceptance Criteria and Reported Device Performance

The document lists performance test items from the "Guidance for Industry and FDA Staff: Display Devices for Diagnostic Radiology" and the methods used. It states that the CL-R813 met "predefined criteria" but does not explicitly provide a table of acceptance criteria with numerical thresholds nor does it report specific numerical performance results for the CL-R813 against those criteria. It only states a qualitative finding of equivalence.

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

Not applicable. This is a display device, not an AI/ML algorithm that processes a "test set" of medical images from patients. The testing involved evaluating the physical characteristics of the monitor hardware.

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

Not applicable. Ground truth for an AI/ML algorithm is not relevant for a display hardware submission.

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. This is a display device, not an AI assistance tool for human readers.

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. For a display device, the "ground truth" is typically defined by industry standards and objective physical measurements (e.g., spectral characteristics of light, spatial resolution patterns). The document references standards like ISO, IDMS, AAPM-TG18, and IEC.

8. The sample size for the training set

Not applicable. This device does not involve a training set for an AI/ML algorithm.

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

Not applicable.

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CL-S600 is intended to be used in displaying and viewing medical images for trained medical practitioners or certified personnel. It is not meant to be used in digital mammography.

30 inch Color LCD Monitor 3280 x 2080 (landscape)
High-luminance color LCD panel, which has wide view angle, is used for this product. It is designed for medical image display.
Luminance stabilization function composed with luminance sensor and luminance control circuit always observes the luminance and makes it stable.
Images are faithfully displayed along grayscale characteristics (DICOM GSDF) based on the calibrated data stored to the lookup table of the monitor.
Luminance and the color mura correction functions will help achieve uniformity on the whole screen.

The provided text describes a 510(k) premarket notification for a medical LCD monitor (JVCKENWOOD 6MP Color LCD Monitor CL-S600). Since this is a submission for a display device, the acceptance criteria and study information provided are related to the technical performance of the monitor itself, rather than the performance of an AI algorithm or diagnostic accuracy.

Therefore, the response below will focus on the device's technical specifications and the tests conducted to demonstrate compliance and substantial equivalence to a predicate device, as presented in the document.

1. Table of Acceptance Criteria and Reported Device Performance

The document presents performance test items in the guidance (which can be inferred as acceptance criteria for this type of device) and the methods used to verify compliance. The actual numerical performance results are not explicitly stated in this high-level summary but are implied to have met the relevant standards.

Note: Items g, h, i, j, k, l are marked "N/A" as they are "For mammography displays," and the device is explicitly stated as "not meant to be used in digital mammography." The compliance is "implied" because the document concludes that "The results of the performance testing and the verification demonstrate that the subject device is substantially equivalent to the currently marketed predicate device."

2. Sample Size Used for the Test Set and the Data Provenance

The document describes physical laboratory tests on the device itself. Thus, the "sample size" is the single device (JVCKENWOOD 6MP Color LCD Monitor CL-S600) undergoing testing. There isn't a "test set" of patient data in the context of an AI algorithm evaluation. The provenance of the data is the physical testing conducted by the manufacturer, JVCKENWOOD Corporation, in Japan.

3. Number of Experts Used to Establish the Ground Truth for the Test Set and the Qualifications of Those Experts

Not applicable for a medical display device's technical performance testing. Ground truth for display performance is established by objective physical measurements against established industry standards (e.g., ISO, AAPM-TG18, IDMS, IEC).

4. Adjudication Method for the Test Set

Not applicable for technical performance testing of a physical device. Objective measurements are used.

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 device is a medical display monitor, not an AI algorithm for diagnostic interpretation. Therefore, no MRMC study or AI assistance evaluation was conducted.

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

Not applicable. This device is a medical display monitor, not an AI algorithm. Its performance is inherent in its hardware and firmware capabilities to accurately display images.

7. The Type of Ground Truth Used

The "ground truth" for the device's technical performance is defined by established international and industry standards for medical displays, such as:

• ISO 13406-2 for pixel defects
• AAPM-TG18 for luminance response and artifacts
• IDMS 1.03 (Information Display Measurements Standard) for various display characteristics
• AAPM-TG196 for gray tracking
• IEC 62563-1 for greyscale chromaticity evaluation
• DICOM GSDF (Grayscale Standard Display Function) for luminance characteristics.

These standards provide objective, quantifiable benchmarks for display performance.

8. The Sample Size for the Training Set

No "training set" is applicable for this device. This is a display monitor, not a machine learning model.

9. How the Ground Truth for the Training Set was Established

No "training set" or corresponding ground truth establishment is applicable for this device.

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CL-S1200 is intended to be used in displaying and viewing medical images for diagnosis by trained medical practitioners or certified personnel. It's intended to be used in digital mammography PACS, digital breast tomosynthesis and modalities including FFDM.

30.9 inch Color Digital Mammography LCD Monitor 4200 x 2800 (landscape)
High-luminance color LCD panel, which has wide view angle, is used for this product. It is designed for medical image display including mammography.
Luminance stabilization function composed with luminance sensor and luminance control circuit always observes the luminance and makes it stable.
Images are faithfully displayed along grayscale characteristics (DICOM GSDF) based on the calibrated data stored to the lookup table of the monitor.
Luminance and the color mura correction functions will help achieve uniformity on the whole screen.
A glass filter protects the surface of the LCD panel.

The provided document is a 510(k) premarket notification for a medical display monitor (JVCKENWOOD 12MP Color Digital Mammography LCD Monitor CL-S1200). It describes the device, its intended use, and a comparison to a predicate device to establish substantial equivalence.

However, the document does NOT contain information about a study proving the device meets clinical acceptance criteria related to AI performance, human reader improvement with AI, or standalone AI performance.

The "acceptance criteria" discussed in the document are limited to physical laboratory tests for display monitor performance (e.g., spatial resolution, pixel defects, luminance, color tracking). These tests are conducted on the device itself (the monitor), not on an AI algorithm that processes medical images.

Therefore, I cannot fulfill all parts of your request because the provided text does not contain the necessary information regarding:

• A table of acceptance criteria for AI performance and reported device performance for AI.
• Sample size used for the test set and data provenance for AI testing.
• Number of experts and qualifications for establishing ground truth for AI testing.
• Adjudication method for AI test set.
• MRMC comparative effectiveness study results (effect size of human readers improvement with AI).
• Standalone AI performance results.
• Type of ground truth used for AI testing.
• Sample size for AI training set.
• How ground truth for AI training set was established.

Based on the provided text, the only "acceptance criteria" and "study" information available is for the display monitor's technical performance, not for an AI algorithm's performance.

Here's what can be extracted regarding the display monitor's acceptance criteria and proof of meeting them:

1. Table of Acceptance Criteria and Reported Device Performance (for the Display Monitor):

The document lists various performance test items and the methods used to evaluate them. It implies that the device met these criteria through testing. While specific numerical results are not provided in a table, the Conclusion states: "The results of the performance testing and the verification demonstrate that the subject device is substantially equivalent to the currently marketed predicate device." This implicitly confirms that the device met the performance standards expected for a device deemed substantially equivalent.

2. Sample size used for the test set and the data provenance (for the Display Monitor):

• Sample Size: This is likely a single device (the JVCKENWOOD 12MP Color Digital Mammography LCD Monitor CL-S1200) that underwent these physical laboratory tests. The concept of a "test set" as in a dataset for AI is not applicable here.
• Data Provenance: The tests are physical laboratory tests conducted by the manufacturer (JVCKENWOOD Corporation) in Japan. The data is prospective, as it's generated specifically for this regulatory submission.

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

• Experts: Not applicable in the context of physical display testing. The ground truth for these tests is based on the physical properties of the display and established objective measurement standards (e.g., ISO, AAPM-TG18, IDMS). Personnel performing the tests would be qualified engineers or technicians.

4. Adjudication method (for the Display Monitor):

• Adjudication Method: Not applicable. These are objective physical measurements per established standards.

5. MRMC comparative effectiveness study results (for the Display Monitor):

• MRMC Study: Not applicable. This document does not describe an MRMC study comparing human reader performance with and without this display monitor, or with AI assistance. It focuses solely on the technical specifications and substantial equivalence of the monitor itself.

6. Standalone (algorithm only without human-in-the loop performance) (for the Display Monitor):

• Standalone Performance: Not applicable. This device is a display monitor, not an AI algorithm.

7. The type of ground truth used (for the Display Monitor):

• Ground Truth: Objective physical measurement standards and industry guidelines (e.g., AAPM-TG18, ISO 13406-2, IDMS 1.03, IEC 62563-1) serve as the "ground truth" or reference for evaluating the display's performance.

8. The sample size for the training set (for the Display Monitor):

• Training Set Sample Size: Not applicable. This device is a hardware product (display monitor), not a machine learning model that requires a training set.

9. How the ground truth for the training set was established (for the Display Monitor):

• Training Set Ground Truth Establishment: Not applicable, as there is no training set for a display monitor.

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MS-S200 is intended to be used in displaying and viewing medical images for diagnosis by trained medical practitioners or certified personnel. It is not meant to be used in digital mammography.

21.3 inch (54cm) Monochrome LCD Monitor
1600 x1200 (landscape)
High-luminance monochrome LCD panel, which has wide view angle, is used for this product. It is designed for medical image display.
Luminance stabilization function composed with luminance sensor and luminance control circuit always observes the luminance and makes it stable.
Images are faithfully displayed along grayscale characteristics (DICOM GSDF) based on the calibrated data stored to the lookup table of the monitor.
It minimizes luminance unevenness by Uniformity Correction Function to achieve the uniformity of luminance on the whole screen.
Quantitative evaluation and visual evaluation are done before the shipment. Quality control along the QC guideline is conducted.

This document, a 510(k) summary for the JVCKENWOOD 2MP Monochrome LCD Monitor MS-S200, does not describe a study involving an AI/CADe device or human readers interpreting medical images. Instead, it is a submission for a medical display monitor, which is a piece of hardware.

Therefore, the information requested in your prompt (acceptance criteria for an AI device, sample sizes, expert ground truth, MRMC studies, standalone performance, etc.) is not applicable to this document.

The document focuses on demonstrating substantial equivalence of the new monitor (MS-S200) to a predicate device (MS25i2) based on technical specifications and performance characteristics, not on clinical performance for diagnosis.

To answer your prompt based on the provided text, I can only extract information related to the monitor's performance criteria, not those of an AI diagnostic tool.

Here's what can be extracted from the document regarding the monitor's performance and validation:

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

The document states: "All items in monitor specification have met the acceptance criteria according to the standard, AAPM-TG18 and ISO 13406-2." It then lists several specifications where the new monitor actually improves upon the predicate device.

Regarding the other points, they are not applicable because this is a hardware device (monitor), not an AI diagnostic algorithm:

2. Sample sizes used for the test set and the data provenance: Not applicable. Performance is based on monitor characteristics, not a clinical data test set.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable. No "ground truth" in the diagnostic sense is established for a monitor. Its performance is measured by objective technical standards.
4. Adjudication method (e.g. 2+1, 3+1, none) 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. This device is not AI and does not involve human readers in this context.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not applicable. This is not an algorithm.
7. The type of ground truth used (expert concensus, pathology, outcomes data, etc): Not applicable.
8. The sample size for the training set: Not applicable. No AI model is being trained.
9. How the ground truth for the training set was established: Not applicable.

In summary, the provided document is a 510(k) submission for a medical display monitor, not an AI diagnostic device. The "study" proving it meets acceptance criteria refers to technical verification against industry standards (AAPM-TG18, ISO 13406-2) and comparison to a predicate device's hardware specifications, not a clinical trial or AI performance evaluation.

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MS-S300 is intended to be used in displaying medical images for diagnosis by trained medical practitioners or certified personnel. It's intended to be used in digital mammography PACS, digital breast tomosynthesis and modalities including FFDM.

21.3 inch Monochrome Digital Mammography LCD Monitor
2048 x 1536 (landscape), 1536 x 2048 (portrait)
■ High-luminance monochrome LCD panel, which has wide view angle, is used for this product. It is designed for medical image display.
■ Luminance stabilization function composed with luminance sensor and luminance control circuit always observes the luminance and makes it stable.
■ Images are faithfully displayed along grayscale characteristics (DICOM GSDF) based on the calibrated data stored to the lookup table of the monitor.
■ It minimizes luminance unevenness by Uniformity Correction Function to achieve the uniformity of luminance on the whole screen.
■ Quantitative evaluation and visual evaluation are done before the shipment. Quality control along the QC guideline is conducted.

The provided text describes the 510(k) premarket notification for the JVCKENWOOD 3MP Monochrome Digital Mammography LCD Monitor MS-S300. It focuses on demonstrating substantial equivalence to a predicate device rather than a comprehensive study proving the device meets specific clinical acceptance criteria.

However, based on the Substantial Equivalence Comparison table and Recommended Physical Laboratory Tests, we can infer some performance aspects and acceptance criteria for the display itself.

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

Since this is a medical display, the "acceptance criteria" largely revolve around meeting or exceeding the technical specifications of the predicate device and adhering to recognized industry standards for medical displays (like AAPM-TG18 and DICOM GSDF). The "reported device performance" is essentially its technical specifications and how they compare to the predicate.

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

The document describes a technical evaluation of a medical display monitor, not a clinical study on medical images. Therefore, "test set" and "data provenance" in the context of clinical images are not applicable here. The testing involves the physical device itself.

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

This information is not explicitly provided. The tests described are objective physical and photometric measurements conducted on the display device, likely by engineers or technicians using specialized equipment and conforming to established standards (e.g., AAPM-TG18, ISO13406-2). There is no mention of human experts establishing "ground truth" for these technical performance metrics.

4. Adjudication method for the test set:

Not applicable in the sense of clinical image review. The evaluation methods are technical measurements against objective criteria and standards.

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 device is a display monitor, not an AI algorithm. Therefore, an MRMC study related to AI assistance would not be relevant.

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

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

7. The type of ground truth used:

For the technical performance of the monitor, the "ground truth" is defined by the objective measurement standards and physical properties specified in documents like AAPM-TG18, ISO13406-2, VESA 2001, and the DICOM GSDF standard. For example, "Luminance Response at 256 digital values by AAPM-TG18" means the measured luminance values at those digital inputs are compared against the expected values defined by the AAPM-TG18 guideline (which aligns with DICOM GSDF).

8. The sample size for the training set:

Not applicable, as this is a physical medical display monitor, not a machine learning model.

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

Not applicable, as this is a physical medical display monitor, not a machine learning model.

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