Search Results

JUSHA-M52C Medical Display is intended to be used for review and analysis by trained medical practitioners in displaying and viewing various kinds of medical images including digital mammography system.

JUSHA-M52C Medical Display is the display system with the high resolution(2048 x 2560), high luminance(700 cd/m² ), and 256 simultaneous shades of gray out of a palette of 4096, 8 DICOM look up table inside, the product is consisted of the following components:

• 21.3 inch, mono-TFT Liquid Crystal Display
• Motherboard HDVI-3M V1.0
• JUSHA-M52C Medical Display software
• Power Adapter
• Data Cable.

This document is a 510(k) Pre-Market Notification from the FDA for a medical display device, the JUSHA-M52C Medical Display. As such, it does not contain a study proving that the device meets specific acceptance criteria in the way a clinical study for a new medical algorithm would.

Instead, the submission aims to demonstrate "substantial equivalence" to a legally marketed predicate device (JUSHA-M52C; K131390, and mentions RadiForce G51 as a comparison for resolution values) by meeting relevant performance standards and safety requirements.

Here's an analysis based on the provided document:

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

The document does not provide a table of acceptance criteria in the sense of specific performance metrics (e.g., sensitivity, specificity, accuracy) for a diagnostic algorithm. Instead, it details the technical specifications of the device and its compliance with relevant medical device standards.

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 applicable as this submission is for a medical display, not an AI/software algorithm that analyzes medical data. Therefore, there is no "test set" of medical images or patient data in the context of evaluation for a diagnostic algorithm. The testing described focuses on hardware and software functionality and compliance with engineering standards.

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 applicable. As explained above, there is no "test set" requiring ground truth established by medical experts for this type of device submission.

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

This information is not applicable. There is no medical image test set requiring adjudication in this 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

This information is not applicable. An MRMC study is relevant for evaluating the impact of an AI diagnostic tool on human reader performance. This submission is for a medical display device, not an AI software.

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

This information is not applicable. This document describes a medical display, which is a hardware device for viewing images, not a standalone AI algorithm. Its function is to present images for human interpretation, not to perform independent diagnostic analysis.

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

This information is not applicable. The device itself does not perform diagnostics requiring ground truth. Its performance validation is based on technical specifications and compliance with safety and performance standards for display technology.

8. The sample size for the training set

This information is not applicable. This device is a medical display, not a machine learning model. Therefore, there is no "training set" in the context of machine learning.

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

This information is not applicable. As stated above, there is no training set for a machine learning model for this device.

Ask a specific question about this device