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The Venue 50 is intended for ultrasound imaging, measurement and analysis of the human body for multiple clinical applications including: Ophthalmic; Fetal/OB; Abdominal (GYN & Urology); Pediatric; Small Organ (breast, testes, thyroid); Neonatal Cephalic; Adult Cephalic; Cardiac (adult & pediatric); Peripheral Vascular; Musculoskeletal Conventional & Superficial; Transvaginal; Intraoperative (abdominal, thoracic and peripheral); Thoracic/Pleural for motion and fluid detection and imaging guidance of interventional procedures.

The Venue 50 device is a compact and portable ultrasound system consisting of a hand-carried console approximately 282mm in height. 274mm in width and 56mm in depth. The console can be docked with a Docking station or mobile Docking cart. It has a 12.1" LCD display with finger-touch user interface. The single-surface screen can be sanitized and cleaned with medical grade disinfectants. Several connectivity options are available including DICOM.

The provided document is a 510(k) Premarket Notification Submission for the GE Healthcare Venue 50 Diagnostic Ultrasound System. It primarily focuses on demonstrating substantial equivalence to predicate devices and does not describe acceptance criteria for device performance based on a study of the device itself. Instead, it outlines the device's intended use, technological similarity to predicate devices, and compliance with various non-clinical safety and performance standards.

Therefore, many of the requested items (e.g., acceptance criteria, reported device performance, sample sizes, ground truth establishment, expert qualifications, MRMC studies, standalone performance, training sets) cannot be extracted or are not applicable from this document, as it explicitly states:

"The subject of this premarket submission, Venue 50, did not require clinical studies to support substantial equivalence." (Page 4)

This implies that the device's safety and effectiveness were demonstrated through a comparison to already cleared predicate devices and adherence to recognized standards, rather than through new clinical performance studies with specific acceptance criteria that would involve human readers, ground truth consensus, or effect sizes of AI assistance.

However, I can provide the information that is present:

1. Table of Acceptance Criteria and Reported Device Performance:

As the document explicitly states no clinical studies were required to support substantial equivalence, there are no specific performance acceptance criteria or reported device performance metrics in terms of clinical accuracy, sensitivity, or specificity. The "acceptance criteria" here are implicitly related to demonstrating substantial equivalence, meaning the device performs similarly to or no worse than the predicate devices in its intended use.

The non-clinical "acceptance criteria" are related to compliance with voluntary standards:

2. Sample size used for the test set and the data provenance: Not applicable. No clinical test set defined to assess performance against specific acceptance criteria.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable. No clinical test set with ground truth established by experts.

4. Adjudication method for the test set: Not applicable. No clinical test set.

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. The device is a diagnostic ultrasound system, not an AI-assisted interpretation tool, and no MRMC study was performed.

6. If a standalone (i.e. algorithm only without human-in-the loop performance) was done: Not applicable. The device is a diagnostic ultrasound system, not a standalone algorithm.

7. The type of ground truth used: Not applicable. No clinical test set with ground truth used.

8. The sample size for the training set: Not applicable. No machine learning algorithm requiring a training set is described.

9. How the ground truth for the training set was established: Not applicable. No machine learning algorithm and thus no training set ground truth established.

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