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EZER Portable X-Ray system is intended to be used by trained dental technicians as an extraoral x-ray source for producing diagnostic x-ray intraoral image receptors. Its use is intended for both adult and pediatric subjects.

EZER Portable X-ray System generates and controls X-ray in order to diagnose of tooth and iaw. It operates on 22.2VDC supplied by a rechargeable Lithum-Ion Polymer battery pack. The X-ray tube head, X-ray controls and power source are assembled into a single hand-held enclosure. EZER Portable X-ray System includes high voltage generator, X-ray tube, a control board (PCB), rechargeable battery, LCD user interface, X-ray beam limiting cone, and a remote control switch (hand switch). Operating principle is that x-ray generated by high voltage electricity into x-ray tube, which penetrates tooth and makes x-ray images on receptor. INTEL stick PC is integrated with EZER so the user can see X-ray image from LCD display without a computer. EZER Portable X-ray System is intended to be used by trained dentists or dental technicians. Its use is intended for both adult and pediatric subjects.

The embedded 7' TFT display in EZER Portable X-ray is not intended to be used for diagnosis.

The provided text is a 510(k) Summary for the EZER Portable X-ray System, which is a device for producing diagnostic dental X-ray images. The document focuses on demonstrating substantial equivalence to a predicate device rather than presenting a clinical study with detailed acceptance criteria and performance metrics for an AI/algorithm-based diagnostic device.

Therefore, the following information regarding acceptance criteria and a study proving device performance will be limited by the nature of the provided text, as it describes a hardware device (X-ray system) and not an AI-driven diagnostic tool that would typically have the requested performance metrics.

There is no information in the provided document about the acceptance criteria and study that proves the device meets specific performance criteria related to the diagnostic accuracy of an AI algorithm.

The document primarily focuses on:

• Safety and Efficacy of the X-ray Hardware: This is demonstrated through adherence to various IEC and EN standards for medical electrical equipment, radiation safety, and electromagnetic compatibility, as well as compliance with 21 CFR regulations for diagnostic X-ray systems.
• Substantial Equivalence: The primary goal of the 510(k) submission is to show that the EZER Portable X-ray System is substantially equivalent to a legally marketed predicate device (Dexcowin ADX 4000W; iRay D4) in terms of indications for use and technological characteristics.

Based on the provided text, I cannot complete the requested tables and sections with specific AI-related performance metrics. However, I can extract the relevant information regarding the device's technical specifications and the type of non-clinical testing performed.

Here's a breakdown of what can be extracted and what cannot be, based on your request and the provided text:

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

The document does not specify "acceptance criteria" in terms of diagnostic accuracy (e.g., sensitivity, specificity for detecting a condition) because EZER is an X-ray source, not a diagnostic interpretation algorithm. Instead, it confirms compliance with safety and performance standards for an X-ray device.

The performance metrics mentioned pertain to the X-ray output and electrical characteristics for the device itself.

Study Proving Device Meets Acceptance Criteria:

The document states: "Testing was performed successfully according to the following standards" and lists multiple IEC, EN, and CFR standards. This non-clinical testing demonstrates that the device itself (the X-ray system) meets the technical and safety performance criteria required for such a device. There is no mention of a diagnostic performance study in the context of disease detection or image interpretation, as the device is an X-ray source.

2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

This information is not applicable and therefore not provided in the document. The testing described is non-clinical performance testing of the hardware device against engineering standards, not a clinical study on diagnostic accuracy involving a test set of patient data.

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)

This information is not applicable and therefore not provided. No clinical "ground truth" was established as this is not a diagnostic algorithm.

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

This information is not applicable and therefore not provided.

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

This information is not applicable and therefore not provided. The device is an X-ray source, not an AI assistance tool for image interpretation.

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

This information is not applicable and therefore not provided. The device is a standalone X-ray system; it does not perform algorithmic diagnosis. The embedded 7" TFT display is not intended to be used for diagnosis.

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

This information is not applicable and therefore not provided.

8. The sample size for the training set

This information is not applicable and therefore not provided. The device is not an AI algorithm that requires a training set.

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

This information is not applicable and therefore not provided.

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