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The DIAGNOcam 2170 Is a diagnostic ald for the detection of open or includent carles lesions above the gingiva and for monitoring the progress of such lesions.

Indications:

• Detection of smooth surface caries
• Detection of occlusal carries
• Detection of proximal carles
• Detection of Initial caries
• Detection of secondary caries
• Detection of cracks

The DIAGNOcam 2170 is a handheld laser fluorescence caries detection device which uses the DIFOTI technology (Digital Imaging Fiberoptic Transillumination) as the functional principle. KaVo DIAGNOcam 2170 delivers images, which are reminiscent of X-rays but which are completely radiation free - by means of a light that is especially adapted to this examination method. The tooth structures allow the passage of light from the entry site to the camera. Areas that block light transmission (e.g. carious lesions) show up clearly as well delimited, dark areas. A digital camera captures the actual situation and makes it visible in real-time on the screen. The USB connector provides electric power to the unit. The DIAGNOcam 2170 will be delivered with a firmware (unit) at the handheld device which is responsible for steering of the camera functions and a computer based software (image) which is responsible to show / display the pictures, store / save the pictures and the possibility of a life stream. The internal laser diode generates an exact wavelength being detectable by the CCD sensor. The DIAGNOcam 2170 follows the international standards for electrical safety and electromagnetic compatibility which are applicable for the use with human beings. The DIAGNOcam 2170 works with a laser wavelength at 788 nm and an output power of 2mW for each laser diode (2 sources). The maximum output power is 21mW/cm2.

Here's an analysis of the provided text regarding the DIAGNOcam 2170, focusing on acceptance criteria and study details:

Overall Conclusion: The provided document does not contain any acceptance criteria or a study proving the device meets them. It is a 510(k) summary, which focuses on demonstrating substantial equivalence to predicate devices, rather than presenting de novo performance studies against pre-defined acceptance criteria.

The document explicitly states: "Clinical testing has not been conducted on this product."

Therefore, I cannot populate the table or provide answers to most of your specific questions as the relevant information is not present in the provided text.

Here's how I can address the prompts based on the available information:

1. Table of Acceptance Criteria and Reported Device Performance

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

• Sample Size for Test Set: Not applicable, as no clinical test data is presented.
• Data Provenance: Not applicable.

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)

• Not applicable, as no clinical test data is presented.

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

• Not applicable, as no clinical test data is presented.

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 comparative effectiveness study was done. The document explicitly states: "Clinical testing has not been conducted on this product." The device is a diagnostic aid, not an AI system.

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

• This question is largely not applicable in the context of this device. The DIAGNOcam 2170 is a hardware device (laser fluorescence caries detection device) that produces images for a dentist to interpret in real-time or from stored images. It's not an "algorithm only" device in the sense of AI performing a diagnosis without human input.
• However, the document mentions "the DIAGNOcam 2170 software has been successfully validated to confirm the performance of the device." This software handles camera functions, image display, storage, and live streaming. This validation is likely focused on the software's functional correctness rather than its diagnostic performance in a standalone capacity for caries detection.

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

• Not applicable, as no clinical test data or ground truth establishment for diagnostic performance is presented.

8. The sample size for the training set

• Not applicable, as no machine learning or AI training is discussed. The device operates on the physical principle of transillumination for caries detection, not through a trained AI model.

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

• Not applicable, as no machine learning or AI training is discussed.

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