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The HeartStart Telemedicine Server software displays patient vitals, waveforms and 12-lead ECG information transmitted from Philips HeartStart defibrillators in remote locations. The HeartStart Telemedicine server allows viewing, diagnostic quality printing, archiving and further distribution of digitized clinical data. The HeartStart Telemedicine Server is also able to forward the 12-lead ECG information into ECG management systems that can process XML format ECG reports such as the TraceMasterVue ECG Management System

The HeartStart Telemedicine Server facilitates transmission of physiological data, waveforms and reports from Philips Defibrillators to a remote server that is located in a facility that is prepared to admit patients being transported by an ambulance.

The provided text describes the Philips HeartStart Telemedicine System and its 510(k) submission. However, it does not include detailed information about acceptance criteria, specific device performance metrics, sample sizes for test or training sets, expert qualifications, or adjudication methods for a study proving the device meets acceptance criteria.

The document states:

• "Verification, validation, and testing activities establish the performance and functionality characteristics of the new device. Testing involved system level tests, integration tests and regression tests from hazard analysis. Pass/Fail criteria were based on the specifications and test results showed substantial equivalence. The results demonstrate that the functionality of the modified 12 lead transfer station meets all performance claims." (Page 1, section 7)

This indicates that testing was performed and pass/fail criteria were used, but the specific criteria and the detailed results demonstrating performance are not provided in this excerpt.

Therefore, I cannot fully answer your request based only on the provided text. Many elements of your request (e.g., a table of acceptance criteria and reported performance, sample sizes, expert qualifications, adjudication methods, MRMC study details, standalone performance, type of ground truth, training set details) are not present.

Here's what I can extract and what is missing, based on your prompt:

1. Table of acceptance criteria and the reported device performance

• Acceptance Criteria: "Pass/Fail criteria were based on the specifications." (Specific criteria not detailed in the provided text).
• Reported Device Performance: "test results showed substantial equivalence. The results demonstrate that the functionality of the modified 12 lead transfer station meets all performance claims." (No specific quantitative performance metrics are provided).

2. Sample sized used for the test set and the data provenance

• Sample Size: Not mentioned.
• Data Provenance (country of origin, retrospective/prospective): Not mentioned.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts

• Not mentioned.

4. Adjudication method for the test set

• Not mentioned.

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 MRMC study is mentioned. The device is a "HeartStart Telemedicine Server" that facilitates data transmission and display, not an AI-assisted diagnostic tool in the sense of improving human reader performance.

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

• The product is described as a "Telemedicine Server." The testing mentioned focuses on "system level tests, integration tests and regression tests" to ensure functionality and performance claims are met, indicating it passed its own operational and functional criteria. However, explicit "standalone performance" in a diagnostic accuracy sense is not discussed as this is a data transmission and display system.

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

• Not mentioned. The testing criteria were "based on the specifications," implying functional and technical correctness rather than diagnostic ground truth.

8. The sample size for the training set

• Not applicable as this is a device for data transmission and display, not a machine learning algorithm that requires a "training set" in the conventional sense.

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

• Not applicable for the same reason as #8.

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