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The Smith & Nephew Tablet Application is indicated for use to provide wireless control of Smith & Nephew compatible surgical and endoscopic devices within the operating room including camera/camera control unit, patient information system, mechanical resection system, fluid management system and RF coblation system. These controls consist of adjusting parameter settings only.

The Smith & Nephew Tablet Application is a software application that provides a Wi-Fi connection between compatible medical devices. Once connected the Tablet Application has the ability to provide limited remote control to the connected devices.

The provided document is a 510(k) premarket notification for the Smith & Nephew Tablet Application, which is a software application for wireless control of surgical and endoscopic devices. However, it does not contain specific acceptance criteria, performance data, or details about a study proving the device meets those criteria. The document focuses on demonstrating substantial equivalence to a predicate device (K192876) based on technological characteristics and intended use.

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

Here's why and what information is missing:

1. Table of acceptance criteria and reported device performance: The document states that "Testing demonstrated that the Smith & Nephew Tablet Application has met the performance specifications" (Page 5, Section H). However, it does not list what those specific "performance specifications" (acceptance criteria) are, nor does it provide the reported device performance against those criteria (e.g., specific accuracy, latency, reliability metrics).
2. Sample size and data provenance: There is no mention of a test set, its sample size, or its provenance (e.g., country of origin, retrospective/prospective).
3. Number/qualifications of experts for ground truth: Since there's no mention of a clinical study or performance evaluation involving human interpretation of data where ground truth would be established by experts, this information is absent.
4. Adjudication method: Similarly, no adjudication method is described because no expert-based ground truth establishment is detailed.
5. Multi-reader multi-case (MRMC) comparative effectiveness study: The document does not describe any study involving human readers or AI assistance for human readers. The device's function is to control surgical parameters, not to assist in image interpretation or diagnosis.
6. Standalone performance: While the software itself performs wirelessly, the concept of "standalone performance" in the context of an AI device (i.e., algorithm only without human-in-the-loop performance) is not applicable here, as its function is control, not interpretation or diagnosis. No specific performance metrics like sensitivity, specificity, or AUC for a diagnostic task are provided.
7. Type of ground truth: No ground truth is described because the device's function is control, not diagnosis or interpretation that would require a ground truth for evaluation. The "performance specifications" it met would likely relate to functional requirements, responsiveness, and connectivity, not diagnostic accuracy.
8. Sample size for the training set: There is no mention of a training set as this is not an AI/ML diagnostic or predictive algorithm.
9. How ground truth for the training set was established: Not applicable, as there's no training set mentioned.

In summary, the provided document is a 510(k) summary for a device that controls surgical equipment wirelessly, not an AI/ML diagnostic or interpretative device. Therefore, the types of studies and performance metrics typically associated with AI/ML devices (like those requiring ground truth, expert readers, MRMC studies, etc.) are not present in this submission. The "performance data" mentioned (Page 5, Section H) refers to "Software validations" and "Cybersecurity testing," which are distinct from the type of performance data requested in the prompt for AI/ML devices.

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