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ETIAM STAR PACS Components™ is a device that receives medical images (including mammograms) and data from various imaging sources. Images and data can be stored, communicated, processed and displayed within the system or across computer networks at distributed locations.

Lossy compressed mammographic images and digitized film screen images must not be reviewed for primary image interpretations. Mammographic images may only be interpreted using an FDA approved monitor that offers at least 5 Mpixel resolution and meets other technical specifications reviewed and accepted by FDA.

ETIAM STAR PACS Components™ are software applications that make possible the capturing, storage, distribution, and networking of medical images at distributed locations. In cases where DICOM images are not directly available to ETIAM STAR PACS Components™, the system can acquire medical images using a DICOM gateway, which generates DICOM-type files. For example, film digitizers obtain images from old film and convert them to meet DICOM standards and stored in an archive. Stored files are transmitted using a network and can be viewed or manipulated from an imaging workstation.

ETIAM STAR PACS Components™ is a software product that handles digital medical images.

The device does not contact the patient, nor does it control any life sustaining devices. A physician, providing ample opportunity for competent human interprets images and information being displayed and printed.

The provided text describes the ETIAM STAR PACS Components™, a Picture Archiving Communications System. However, it does not contain any information about acceptance criteria, device performance studies, sample sizes for test or training sets, expert qualifications, or ground truth establishment.

The document is a 510(k) summary of safety and effectiveness information, which primarily focuses on demonstrating substantial equivalence to a predicate device. It describes the device's function and indications for use, but not the detailed performance evaluation studies typically associated with acceptance criteria.

Therefore, I cannot provide the requested information from the given text.

The following information is NOT available in the provided document:

• A table of acceptance criteria and the reported device performance
• Sample sizes used for the test set and the data provenance
• Number of experts used to establish the ground truth for the test set and their qualifications
• Adjudication method for the test set
• If a multi reader multi case (MRMC) comparative effectiveness study was done, or the effect size of human readers improvement with AI vs without AI assistance
• If a standalone (algorithm only without human-in-the-loop performance) was done
• The type of ground truth used (expert consensus, pathology, outcomes data, etc.)
• The sample size for the training set
• How the ground truth for the training set was established

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