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The J-MAC VOX/BASE for Windows is a stand alone software product which allows medical professionals to view, retrieve, store, import, process and transmit medical images over networks or phone lines. This type of product is commonly referred to as a Picture Archival and Communication System (PACS). It is intended to display various image data used in a hospital, clinic, physician's office and other health care settings. It handles data from CR, CT, DS, MR, NM, US, ES, RG and other modalities.

The J-MAC VOX/BASE for Windows is a stand alone software product which allows medical professionals to view, retrieve, store, import, process and transmit medical images over networks or phone lines. This type of product is commonly referred to as a Picture Archival and Communication System (PACS). The software consists of four modules: Query, Receive, View and Manager.

This document is a 510(k) summary for the J-MAC VOX/BASE System, a Picture Archival and Communication System (PACS) software. It focuses on demonstrating substantial equivalence to a predicate device rather than presenting a performance study with specific acceptance criteria and results.

Therefore, the requested information regarding acceptance criteria, study details, sample sizes, ground truth establishment, and MRMC studies cannot be extracted from the provided text.

Here is what can be extracted or inferred based on the document's content:

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

This information is not provided because the submission is for substantial equivalence to a predicate device, not for proving specific performance metrics against defined acceptance criteria through a clinical or performance study. The "performance" assessment is based on comparing features and intended use with the 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):

Not applicable. No formal test set or clinical study is described. The submission focuses on device features and compliance with 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):

Not applicable. No test set requiring expert-established ground truth is mentioned.

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

Not applicable. No test set or expert adjudication is described.

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. This document does not mention any MRMC study. The device is a PACS system, not an AI-powered diagnostic tool, and the submission predates widespread AI in medical imaging.

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

The device itself is a "stand alone software product" in the sense that it functions independently as a PACS system. However, this refers to its operational independence, not to a "standalone performance study" in the context of an algorithm's diagnostic accuracy. There's no mention of a performance study for the algorithm's diagnostic capabilities.

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

Not applicable. No ground truth is established or used for performance evaluation in this submission.

8. The sample size for the training set:

Not applicable. This is not a submission for an AI/machine learning algorithm requiring a training set.

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

Not applicable. No training set is mentioned.

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