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Soreal Press is indicated for single-unit anterior or posterior prostheses and for three-unit prostheses, such as veneers, inlay/onlay, partial crowns, anterior crowns, posterior crowns, using the hot press technique. Soreal CAD is indicated for single-unit anterior or posterior prostheses and for three-unit prostheses, such as veneers, inlay/onlay, partial crowns, anterior crowns, posterior crowns, using the CAD/CAM system.

Our products are divided into Soreal Press and Soreal CAD. Soreal Press is put into the porcelain casting furnace and form it by hot pressing at 915-930 °C, and treatment by sandblasting and glazing. Soreal CAD is cut by grinding equipment with wet processing, and put into the porcelain casting furnace at 840-850°C for 30 min to secondary crystallization treatment. Then dye it. They are all composed of SiO2, Li2O, K2O, P2O5, Al2O3 and other oxides. They have a variety of colors, and users can choose the right color to match the patient's natural teeth. In general, our products are also called Dental glass ceramic.

The provided document is a 510(k) Summary for a dental ceramic device (Soreal Press/Soreal CAD) and focuses on demonstrating substantial equivalence to a predicate device, rather than providing a performance study of an AI/ML powered device. Therefore, many of the requested criteria related to AI/ML device performance (like multi-reader multi-case studies, effect size of AI assistance, expert ground truth establishment for AI training/testing) are not applicable or findable in this document.

However, I can extract information related to the acceptance criteria for a non-AI/ML medical device and the study that proves it meets these criteria, as detailed in the document.

Here's a breakdown of the available information:

Acceptance Criteria and Reported Device Performance

The acceptance criteria for this dental ceramic device are based on the requirements of ISO 6872:2015 "Dentistry – Ceramic materials" and ISO 10993 "Biocompatibility." The document provides a table summarizing these, which I have reproduced below.

Table of Acceptance Criteria and Reported Device Performance

Study Details (Based on the Provided Document)

1. Sample size used for the test set and the data provenance:

   • The document does not explicitly state the sample sizes for each specific test (e.g., how many samples were used for flexural strength, chemical solubility, etc.). It only provides the measured data points obtained from these tests.
   • Data Provenance: The tests were "Non-clinical data" performed according to ISO standards. The origin (country) of the test data is not specified, but the applicant company is Shenzhen UP3d Technology Co., Ltd. in China. The data is retrospective, as it was generated to support a 510(k) submission.

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

   • This is not applicable as the device is a dental ceramic, not an AI/ML-powered diagnostic device. "Ground truth" in this context refers to physical and chemical properties measured in a lab, not expert interpretations of medical images or data.

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

   • Not applicable for physical and chemical property tests of a material. The tests follow standardized protocols (ISO standards).

4. 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. This is not an AI-powered device.

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

   • Not applicable. This is not an AI-powered device.

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

   • The "ground truth" for this device is the physical, chemical, and biological properties measured according to international standards (ISO 6872:2015 for dental ceramic materials and ISO 10993 for biocompatibility). This involves laboratory measurements and assessments, not clinical "ground truth" derived from patient outcomes or expert consensus on medical images.

7. The sample size for the training set:

   • Not applicable in the context of an AI/ML training set, as this is a non-AI/ML medical device. For material development, internal R&D would involve extensive material science work, but a specific "training set" in the AI sense is not relevant here.

8. How the ground truth for the training set was established:

   • Not applicable for a non-AI/ML medical device. For material development, the "ground truth" of material properties is established through adherence to material science principles, experimental methodology, and international standards.

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