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This product is suitable for making invisible orthodontic appliances by additive manufacturing (light curing 3D printing) process. The orthodontic appliance is designed for orthodontic treatment. It uses continuous gentle force to adjust tooth position, correct malocclusion, and maintain the results of completed orthodontic treatment.

It can also be used for printing splints and night guards.

Additively Manufactured Aligner Resin is custom plastic aligner system which are a series of doctor prescribed clear removable aligners that are used as alternative treatment for the alignment of maloccluded or misaligned teeth. This series of aligners gently move the patient's teeth in small increments from their original state to a treated state.

Additively Manufactured Aligner Resin is a light-curing resin used to print orthodontic appliances. The resin is a light yellow transparent liquid. The appliance printed by a 3D printer is de-supported, cleaned and post-cured to obtain an orthodontic appliance that can correct the patient's malocclusion. This product is a light-curing 3D printing resin composed of acrylate resin oligomers and acrylate monomers as well as initiators and additives.

Additive manufacturing (light cured) orthodontic resin is a light cured acrylic resin commonly used in the manufacture of orthodontic appliances. The resin is stored in a black HDPE bottle according to the weight of the resin liquid. The color of the resin is colorless or yellowish liquid, polymerized by UV light at 385 nm or 405 nm.

The provided FDA 510(k) clearance letter details the clearance of an "Additively Manufactured Aligner Resin." This document is for a material, not a diagnostic AI device. Therefore, the information typically requested in a description of an AI device's acceptance criteria and study proving its performance (e.g., sample sizes for test and training sets, number of experts establish ground truth, MRMC studies, standalone performance) is not applicable to this submission.

The acceptance criteria and supporting studies for this material device primarily focus on bench testing (physical and mechanical properties), biocompatibility, sterility, and shelf-life. The purpose of these tests is to demonstrate that the new aligner resin is safe and effective for its intended use, comparable to already marketed predicate devices.

Here's an interpretation of the relevant information provided:

Acceptance Criteria and Performance of "Additively Manufactured Aligner Resin"

As this is a material device, the "acceptance criteria" are based on meeting established international standards for dental materials and demonstrating comparable or superior performance to existing predicate devices. The "study that proves the device meets the acceptance criteria" refers to the non-clinical bench testing, biocompatibility testing, and shelf-life testing performed.

1. Table of Acceptance Criteria and Reported Device Performance

The primary standard referenced for mechanical characteristics is ISO 20795-2:2013 Dentistry – Base polymers – Part 2: Orthodontic base polymers. The acceptance criteria for each property are implicitly defined by the requirements of this standard, and the device's performance is reported as meeting these requirements or being comparable to predicate devices.

*Note: For Flexural Modulus and Ultimate Flexural Strength, the subject device's performance was statistically significantly higher than the predicate, which is considered an improvement and not an adverse difference in terms of safety or effectiveness for the material properties. For Water Solubility and Sorption, slight differences were observed but all conformed to the ISO standard.

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

The document does not specify the exact sample sizes for each mechanical property test (e.g., number of specimens tested for flexural strength). This level of detail is typically found in the full testing report, not the 510(k) summary. However, tests were conducted as "bench testing" meaning in a laboratory setting. The data provenance is implied to be from the manufacturer's internal testing facilities, Aidite (Qinhuangdao) Technology Co., Ltd., which is based in China. The testing is retrospective in the sense that it's pre-market validation performed on manufactured material samples.

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

This question is not applicable as this is a material device and not an AI or diagnostic device that requires expert-established ground truth for a test set. Ground truth for material properties is established by objective physical and chemical testing methods adhering to international standards (e.g., ISO, ASTM).

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

This question is not applicable as there is no human interpretation or subjective assessment being performed that would require an adjudication method. The testing results are quantitative measurements.

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 question is not applicable. An MRMC study is relevant for diagnostic AI devices where human readers (e.g., radiologists) interpret images with and without AI assistance. This submission is for a dental material.

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

This question is not applicable. There is no algorithm or software for standalone performance evaluation in this material device submission.

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

The "ground truth" for this material device is established by objective, standardized laboratory testing methods against pre-defined specifications and international material standards (e.g., ISO 20795-2:2013). This is analogous to a "gold standard" for material properties.

8. The sample size for the training set

This question is not applicable. This is a material device, not an AI/machine learning model, and therefore does not have a "training set" in the computational sense.

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

This question is not applicable for the same reason as point 8.

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Biomic Color Opaque is liquid used for coloring pre-sintered zirconia restorations. It is used for the internal surface of dental zirconia material prosthesis.

Biomic Color Opaque is a liquid primarily composed of Methylacryloyl propyl trimethoxy silane, deionized water, 1, 3-butanediol, ferric chloride, citric acid, cerium nitrate, erbium nitrate, cobaltous nitrate, manganous acetate, and aluminum nitrate.

This product is designed for use on the internal surface of dental zirconia material prostheses. It penetrates tightly with the zirconia surface, forming an extremely thin shade layer that reduces the internal surface permeability of the zirconia material prosthesis. The devices are intended to be used solely by dental technicians for the fabrication of zirconia restorations for individual dental patients.

For staining, the zirconia materials must be immersed into the staining solution or brushed with the liquid before sintering at high temperature. The staining solution consists of two components: Type I - a color component (A、B、C、D、W、L、M、R、S、X), and Type II - an OP component, 1:1 collocation is recommended. These components are mixed together for use on the zirconia material to achieve the desired shade.

The provided FDA 510(k) clearance letter and its accompanying summary for the "Biomic Color Opaque" device do not contain information about clinical studies or performance data related to AI/algorithm-driven performance, ground truth establishment, or multi-reader multi-case (MRMC) studies.

The document explicitly states under Section 7.0, "Summary of Clinical Test," that "Clinical testing was not required for this submission." This indicates that the device's clearance was based on non-clinical data (bench testing, biocompatibility, sterility, shelf-life) and a comparison to a predicate device, not on AI/algorithm performance. The device itself is a "Porcelain Powder For Clinical Use" (specifically a pre-sintered zirconia coloring liquid), not an AI-driven diagnostic or image analysis tool.

Therefore, it is impossible to provide the requested information regarding acceptance criteria, study details, sample sizes, expert involvement, and ground truth for an AI/algorithm-driven study based solely on the provided text.

However, I can extract the acceptance criteria and performance related to the physical and chemical properties of the device, as that is the type of testing described.

Here's a summary of the acceptance criteria and performance as described for this specific device (a coloring liquid), not for an AI algorithm:

Acceptance Criteria and Reported Device Performance (Non-AI Device)

Regarding the AI/Algorithm-Specific Questions:

Since the device is a dental coloring liquid and not an AI-driven device, the following information is not applicable or not provided in the document:

• Sample size used for the test set and the data provenance: Not applicable; no AI test set described.
• Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable; no ground truth for AI performance required.
• Adjudication method (e.g., 2+1, 3+1, none) for the test set: Not applicable.
• 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.
• If a standalone (i.e., algorithm only without human-in-the-loop performance) was done: Not applicable.
• The type of ground truth used (expert consensus, pathology, outcomes data, etc.): Not applicable to an AI device. The ground truth for this device's performance relates to its physical/chemical conformity to standards.
• The sample size for the training set: Not applicable; no AI training set.
• How the ground truth for the training set was established: Not applicable.

In conclusion, the provided FDA document details the regulatory clearance for a traditional medical device (dental coloring liquid) based on its physical, chemical, and biological properties, and its substantial equivalence to a predicate device. It does not pertain to the evaluation of an AI-powered medical device.

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Additive Manufacturing (Light Curing) Crown Bridge Resin is a light-cured resin indicated for the fabrication of permanent single crowns in the anterior and posterior region, denture teeth, inlays, onlays, veneers and implant crown. It is also used for long-term provisional crowns and bridges.

Additive Manufacturing (Light Curing) Crown Bridge Resin is a light-curing, hybrid dental material, composed of methacrylic acid esters, inorganic filler, photoinitiator, organic pigments, inorganic pigments and additives. It is Liquid resin for dental 3D printing of permanent single crowns in the anterior and posterior region, denture teeth, inlays, onlays, veneers and implant crown. It is also used for long-term provisional crowns and bridges. The Subject device is used by a dentist or dental technician for the CAD/CAM manufacturing of temporary or permanent dental restorations. For use in Digital Light Processing (DLP)- 3D printers utilizing wavelengths at 385nm or 405nm.

The Subject device is packaged in black plastic bottles made of high density polyethylene (HDPE) according to the weight of the resin liquid.

There are different shades A1, A2, A3, A3.5, A4, B1, B2, B3, B4, C1, C2, C3, C4, D2, D3, D4, BL1, BL2, BL3, BL4, and the different shades are reflected in the different colors of finished restorations.

The provided FDA 510(k) clearance letter and summary describe a dental resin, not an AI/software as a medical device (SaMD). Therefore, the information required for explaining AI/SaMD acceptance criteria and studies (such as diagnostic performance metrics, reader studies, ground truth establishment, training/test set details, etc.) is not present in this document.

The document focuses on the physical, mechanical, and biocompatibility properties of a dental manufacturing resin. As such, I cannot extract the requested information regarding AI/SaMD performance studies from this provided text.

Here's a breakdown of why the requested information cannot be provided based on the input:

• Device Type: The device, "Additive Manufacturing (Light Curing) Crown Bridge Resin," is a material used for 3D printing dental restorations. It is not an AI algorithm or software.
• Study Type: The studies performed are bench tests (Non-clinical Test Conclusion) evaluating material properties (e.g., flexural strength, water sorption, biocompatibility) against established ISO standards, and shelf-life testing. These are not studies to prove the performance of an AI model.
• Acceptance Criteria & Performance: The acceptance criteria are explicitly tied to physical and mechanical properties (e.g., Flexural Strength ≥ 50 MPa as per ISO 10477:2020), not diagnostic accuracy or other AI-related metrics.
• Missing Information Related to AI/SaMD: All specific points requested in your prompt (sample size for test/training sets, experts for ground truth, adjudication methods, MRMC studies, standalone performance, type of ground truth, effect size) are entirely absent because they are not applicable to the clearance of a dental resin material.

In summary, the provided document does not contain the information necessary to describe the acceptance criteria and study that proves an AI/SaMD device meets its acceptance criteria. The document pertains to a physical dental material, not an artificial intelligence product.

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Dental Zirconia Ceramic are used for dental restorations using different CAD/CAM or manual milling machines. All blanks are processed through dental laboratories or by dental professionals.

Dental Zirconia Ceramic is pre-shaded zirconia, and it's composed of yttria-stabilized zirconia. It contains ZrO2+HfO2+Y2O3+Al2O3 and very small amount of additional inorganic pigments (Fe2O3+Er2O3+Co3O4). The inorganic pigments generate the color on the restorations, after sintering at dental labs, that matches natural color of patient's teeth.

Dental Zirconia Ceramic has 19 models mainly according to the flexural strength (i.e. ≥600Mpa and ≥800Mpa) and the shade uniformity in the whole blank (i.e. monolayer and multilayer). Each model also has several available shade variations. And it also offers various shapes and dimensions suitable for different milling systems.

The proposed device is processed into the dental restorations such as crowns, bridges, veneers, inlays and onlays based on the anatomical rendering of the patient's teeth using CAD/CAM (computer aided design / computer aided manufacturing) method or manual milling method.

The proposed device is a single-use device, provided non-sterile, and its performance conforms to ISO 6872:2015/AMD 1:2018 Dentistry: Ceramic Materials.

I'm sorry, but the provided text is a 510(k) premarket notification letter from the FDA regarding a "Dental Zirconia Ceramic" device. This document does not contain the specific information you requested regarding acceptance criteria and a study proving device performance, particularly related to AI/software aspects.

The document discusses:

• Device Name: Dental Zirconia Ceramic
• Regulation Number: 21 CFR 872.6660 (Porcelain Powder For Clinical Use)
• Regulatory Class: Class II
• Product Code: EIH
• Intended Use: Dental restorations using CAD/CAM or manual milling machines.
• Non-clinical Test Conclusion: Physical and mechanical properties evaluated according to ISO 6872:2015/AMD 1:2018 and ISO 13356:2015. Biocompatibility testing performed.
• Technological Characteristics: Yttria-stabilized zirconia composition, inorganic pigments for color.
• Comparison to Predicate Device: Notes similarities in intended use, patient population, principle of operation, and mechanism of action. Highlights differences in the number of models offered (new models added).
• Conclusion: Substantial equivalence to the legally marketed predicate device based on comparison and analysis.

However, it does not provide:

1. A table of acceptance criteria and reported device performance in a measurable format for software or AI.
2. Sample size used for the test set and data provenance for a software algorithm.
3. Number of experts used to establish ground truth and their qualifications.
4. Adjudication method.
5. Multi-Reader Multi-Case (MRMC) comparative effectiveness study information (human readers improve with/without AI assistance).
6. Standalone (algorithm-only) performance.
7. Type of ground truth used (e.g., pathology, outcomes data).
8. Sample size for the training set.
9. How ground truth for the training set was established.

The device described is a ceramic material for dental restorations, not an AI or software-based medical device. Therefore, the specific types of studies and criteria you're asking about (MRMC, standalone performance, training/test sets, ground truth establishment for AI) are not present in this document.

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Porcelain Powder can be used to make facings and veneers of customized denture crowns. It is suitable for adults over 18 years old.

This product includes Porcelain Powder, Stain/Glaze, Stain/Glaze-A and Modeling Fluid.

Enamel/ Modifier is Enamel porcelain, its function is to make adjusted porcelain powder gently stacked in the incisal aimed at shape, and stack from incisal to the body, covering dentin porcelain:

Stain/Glaze and Stain/Glaze-A is Enamel layer, its function is to coat with a thin layer of glaze on the surface of the finishing porcelain crown to achieve the required color and gloss of natural teeth.

Modeling Fluid: A dental ceramic powder is mixed in order to shape or model it into its required form prior to firing

The provided text is an FDA 510(k) summary for a dental product, "Porcelain Powder." It outlines the product's classification, intended use, and a comparison to a predicate device to establish substantial equivalence.

Crucially, this document is for a dental material (Porcelain Powder), not a medical device software (MDSW) or an AI/ML-driven device. Therefore, the information requested in your prompt regarding acceptance criteria, study details, ground truth, expert adjudication, MRMC studies, and standalone performance for AI/ML devices is not present in this regulatory submission.

The document states: "Clinical testing was not required for this submission." This indicates that no human performance or comparative effectiveness studies were conducted for this traditional material device. The "Non-clinical Test Conclusion" section primarily refers to bench testing for physical and mechanical properties, and biocompatibility testing.

To answer your prompt with the provided input, I must state that the requested information (acceptance criteria, study details for AI/ML device performance) is not applicable to the Porcelain Powder device and is not contained within this 510(k) summary.

Therefore, I cannot populate the table or provide the requested details about acceptance criteria, study design, ground truth, or expert involvement as this information pertains to a different type of medical device (AI/ML or diagnostic software) than the "Porcelain Powder" described in the provided text.

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Additively Manufactured Denture Resin is a light-cured resin indicated for the fabrication of all types of denture bases, for instance full and partial removable dentures.

Additively Manufactured Denture Resin is intended for continuous use in the oral environment, exclusively for professional dental work.

Additively Manufactured Denture Resin can be used in combination with a DLP 3D printers utilizing wavelengths at 385nm or 405nm. A 3D-printer is not part of the device.

Additively Manufactured Denture Resin is a light-cured one-component materials for dental professional use only and intended for the fabrication of full and partial removable dentures. This Product is a liquid photo-curable material that is polymerized, by the photo-initiator contained in the resin. For use in Digital Light Processing (DLP)-3D printers utilizing wavelengths at 385nm or 405nm. The specifications of this product are divided into 500g, 1000g, 5kg and 10kg according to the weight of the resin liquid.

The provided document is a 510(k) summary for a medical device called "Additively Manufactured Denture Resin." It presents information about the device's intended use, technological characteristics, and a comparison to a predicate device to establish substantial equivalence.

Based on the information provided, here's a breakdown of the acceptance criteria and study details:

Device: Additively Manufactured Denture Resin

1. Table of Acceptance Criteria and Reported Device Performance:

The document refers to adherence to the international standard ISO 20795-1 Dentistry - Base polymers - Part 1: Denture base polymers for physical and mechanical properties. The specific acceptance criteria within this standard are not explicitly listed in a table, but the document states:

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

The document states "Bench Testing: Physical and mechanical properties of the subject device were evaluated according to FDA-recognized version ISO 20795-1 Dentistry - Base polymers - Part 1: Denture base polymers." It also mentions "Biocompatibility Testing was performed according to FDA currently-recognized versions of biocompatibility consensus standards..."

However, the specific sample sizes for these tests are not provided in the document. The data provenance is related to laboratory bench testing and biocompatibility testing, indicating a controlled laboratory environment rather than direct patient data. The origin of the testing (e.g., country) is not specified beyond the manufacturer being from China.

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

This information is not applicable in this context. The document describes the testing of a material's physical, mechanical, and biological properties against established international standards (ISO 20795-1, ISO 10993 series). Ground truth in this case is defined by these standards and the protocols for carrying out the tests, rather than by expert consensus on clinical cases.

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

This is not applicable. The testing involves objective measurements against predefined criteria in laboratory settings, not clinical interpretation requiring adjudication.

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 is not applicable. The device is a "Denture Resin," a material used for fabricating dental prostheses, not an AI or imaging diagnostic tool that would involve human readers or AI assistance.

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

This is not applicable. The device is a material, not a software algorithm.

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

The ground truth for the performance claims for the denture resin is based on established material science standards and biocompatibility guidelines (ISO 20795-1, ISO 10993, ISO 7405). These standards define the test methods and acceptance limits for various physical, mechanical, and biological properties.

8. The sample size for the training set:

This is not applicable. The device is a material product, not a machine learning model that requires a training set.

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

This is not applicable as there is no training set for this type of device.

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Dental Glass Ceramics Blocks are indicated for fabricating all-ceramic restorations such as veneers, inlay/ onlay, partial crowns, anterior crowns, posterior crowns, using the hot press technique or CAD/ CAM system.

Dental Glass Ceramics Blocks are derived from dental porcelain powder that has been processed into their final net shapes. These blanks are then being further fabricated (using hot press or CAD/CAM technologies) into all-ceramic restorations such as veneers, inlay/ onlay, partial crowns, anterior crowns, posterior crowns. The ceramics material is composed of SiO2, Li2O, K2O3 and other oxides. It also contains inorganic pigments to provide different shades on the product surface. It has three model: HT,LT,ST, and totally 23 colors(A1,A2,A3,A3.5,A4,B1,B2,B3,B4,C1,C2, C3,C4,D2,D3,D4,BL1,BL2,BL3,BL4, OM1, OM2 and OM3).

This FDA 510(k) summary is for a dental device (Dental Glass Ceramics Blocks) and focuses on demonstrating substantial equivalence to a predicate device, rather than providing a detailed study report with acceptance criteria and performance metrics for a novel AI/software device. Therefore, much of the requested information regarding AI/software performance studies (like sample sizes for test sets, data provenance, number of experts for ground truth, adjudication methods, MRMC studies, standalone performance, and training set details) is not applicable to this document.

However, I can extract the relevant information regarding acceptance criteria and device performance based on the provided text for this specific type of medical device.

Device Name: Dental Glass Ceramics Blocks (HT,LT,ST)

Acceptance Criteria and Reported Device Performance:

Study to Prove Device Meets Acceptance Criteria:

A non-clinical test and biocompatibility testing were conducted.

• Physical and mechanical properties of the subject device were evaluated according to ISO 6872:2015/AMD 1:2018. This standard classifies the device into:
  • Type II: All other forms of ceramic products.
  • Class 4: Monolithic ceramic for prostheses involving partially or fully covered substructure.
  • The document states that the new model "ST" and the existing models (HT, LT, which correspond to the predicate device's models) were tested and found to have physical/mechanical properties that met the requirements of ISO 6872.
• Biocompatibility testing was performed to verify the equivalent safety of the materials used. The results comply with ISO 10993-1:2018 and FDA Guidance.

Information Not Applicable to this Submission (as it is not an AI/software device):

• Sample size used for the test set and data provenance: Not applicable. This is a physical material device, not a software/AI system. The testing involved material properties, not a "test set" of data in the AI sense.
• Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable. Ground truth for material properties is established by standardized physical and chemical testing, not expert consensus on medical images or patient data.
• Adjudication method for the test set: Not applicable.
• If a multi-reader multi-case (MRMC) comparative effectiveness study was done: Not applicable. This is not an AI-assisted diagnostic or predictive device.
• If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not applicable.
• The type of ground truth used: For material properties, the "ground truth" is defined by the objective measurements obtained through standardized physical, mechanical, and chemical tests to meet the specified ISO standard. For biocompatibility, it's defined by compliance with ISO 10993-1 and FDA guidance through specific biological evaluation tests.
• The sample size for the training set: Not applicable (no AI/machine learning involved).
• How the ground truth for the training set was established: Not applicable.

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Denture Base Resin is used for the fabrication of removable dentures.

The Denture Base Resin mainly consist of denture base resin (powder), polymethyl methacrylate (PMMA), methyl methacrylate, ethylene glycol dimethacrylate, titanium dioxide, ferric oxide, iron oxide yellow and ferric tetroxide. The resin block is milled using the CAD/CAM technique to form the removable dentures. The product combines the prosthetic denture teeth with the denture base.

The provided document is a 510(k) premarket notification for a medical device called "Denture Base Resin." This type of submission focuses on demonstrating substantial equivalence to a predicate device, rather than proving novel clinical effectiveness or safety through new clinical trials. Therefore, the information typically requested in your prompt regarding AI/ML device performance (e.g., acceptance criteria for a specific AI metric, human-in-the-loop performance, large test sets, expert ground truth adjudication) is not applicable to this submission.

This document describes a traditional dental material. The performance data presented are for material properties, not an AI/ML algorithm.

Here's why many of your detailed questions cannot be answered by this document:

• AI/ML Device: This is not an AI/ML device. It's a physical material used for fabricating dentures.
• Acceptance Criteria for AI Performance: The acceptance criteria are for physical material properties as defined by ISO standards, not for AI metrics like sensitivity, specificity, AUC, or F1-score.
• Sample Size for Test Set (AI): There's no AI test set. Instead, there are samples of the material tested for its physical and chemical properties.
• Data Provenance (AI): Not applicable. The "data" are laboratory measurements of material properties.
• Experts for Ground Truth (AI): Not applicable. Ground truth for material properties is established through standardized laboratory testing methods.
• Adjudication Method (AI): Not applicable.
• MRMC Study (AI): Not applicable. This refers to human reader performance with/without AI assistance for diagnostic tasks, which is irrelevant here.
• Standalone Performance (AI): Not applicable.
• Type of Ground Truth (AI): For this device, "ground truth" refers to the measured physical and chemical properties of the material against established standards (e.g., ISO, FDA guidance).
• Training Set (AI): Not applicable. This device is not developed using machine learning.
• Ground Truth for Training Set (AI): Not applicable.

Based on the provided document, here's what can be extracted regarding the "acceptance criteria" (which are performance specifications for the material) and its "study" (which are non-clinical bench tests):

1. Table of Acceptance Criteria and Reported Device Performance

The acceptance criteria are implicitly defined by the relevant ISO standards (ISO20795-1: 2013, ISO 4049: 2019, ISO 7491: 2000) and the comparison to the predicate device. The performance data demonstrate compliance with these standards and substantial equivalence.

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

• Sample Size: The document does not specify the exact sample sizes for each bench test conducted (e.g., how many specimens for flexural strength). It generally states that "Performance testing were conducted to verify that the subject device met all design specifications." Specific sample sizes would be detailed in the full test reports, which are not part of this summary.
• Data Provenance: The tests are non-clinical bench tests performed in a laboratory setting, presumably by the manufacturer (Aidite (Qinhuangdao) Technology Co., Ltd) or a contracted lab. The country of origin for the data is implicitly China, as the manufacturer is based there. The data are retrospective in the sense that they were collected prior to the submission.

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

• Not applicable as this is not an AI/ML device requiring expert interpretation for ground truth. The "ground truth" for material properties is established through standardized and validated laboratory testing procedures as per ISO standards.

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

• Not applicable. This concept applies to human reader studies often seen with diagnostic AI/ML devices, not material property testing.

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, an MRMC comparative effectiveness study was not done. This is not an AI/ML device.

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

• No, a standalone algorithm performance study was not done. This is not an AI/ML device.

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

• The "ground truth" for this device's performance is derived from standardized laboratory measurement methods as described in the cited ISO standards (e.g., ISO20795-1 for denture base polymers, ISO 4049 for polymer-based restorative materials, ISO 7491 for color stability) and biocompatibility testing according to ISO 10993-1. Comparison is also made to the performance characteristics of the predicate device.

8. The sample size for the training set:

• Not applicable. This device is not an AI/ML algorithm that requires a training set.

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

• Not applicable.

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Dental Ceramic Blocks are indicated for fabrication of inlays onlays, aminate veneers, anterior and posterior full crown restorations, and implant crowns and bridges by dental professionals and manufacturers using a dental CAD/CAM system.

Dental Ceramic Blocks consist of methacrylate, benzoyl peroxide, barium glass powder and pigmen to form a solid block of material. The unique marriage of the materials creates a dual-network hybrid, which lends the positive physical properties of each individual material to the other. This non-sterile material is milled in a dental CAD/CAM machine into restorative form for single patient use. Dental Ceramic Blocks is provided as non-sterile.

The provided text is a 510(k) Premarket Notification for a dental device, "Dental Ceramic Blocks." This document does not include information about AI/ML device performance or a study demonstrating the device meets acceptance criteria related to AI/ML.

The device described is a physical material (dental ceramic blocks) used to fabricate dental restorations. The "acceptance criteria" and "study that proves the device meets the acceptance criteria" refer to the non-clinical performance testing of these physical blocks, not an AI/ML algorithm.

Therefore, I cannot provide the requested information regarding AI/ML device performance, ground truth establishment, expert adjudication, or MRMC studies because the provided document does not pertain to an AI/ML device.

However, I can extract the information related to the physical device's performance acceptance criteria and proof if that is what you are looking for.

For the physical device (Dental Ceramic Blocks), here's what the document states regarding acceptance criteria and performance:

1. Table of acceptance criteria and reported device performance:

Note: The document explicitly states "Although the results have slightly difference, they meet the acceptance criteria. Therefore, this difference is considered not to affect the Substantially Equivalency (SE) between the proposed and predicate devices" for Flexural Strength and Radioactive properties.

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

• The document does not specify sample sizes for non-clinical performance and biocompatibility tests. It only lists the standards followed (e.g., ISO 4049, ISO 10993 series).
• Data provenance: Not explicitly stated, but implies lab testing. No information on country of origin of data. These are non-clinical / bench tests, not patient data trials.

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

• Not applicable. This is for a physical device, not an AI/ML diagnostic or measurement device. Ground truth is established by laboratory measurement standards (e.g., ISO standards).

4. Adjudication method for the test set:

• Not applicable. This is for a physical device, not an AI/ML diagnostic or measurement device.

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:

• Not applicable. This document is not about an AI/ML device.

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

• Not applicable. This document is not about an AI/ML device.

7. The type of ground truth used:

• For the physical properties (Flexural Strength, Radiopacity), ground truth is established by standardized laboratory measurement methods outlined in ISO 4049 and ISO 7491.
• For Biocompatibility, ground truth is established by adherence to ISO 10993 series standards test methods (e.g., cytotoxicity, irritation, systemic toxicity, genotoxicity).

8. The sample size for the training set:

• Not applicable. This document is not about an AI/ML device, so there is no "training set."

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

• Not applicable. This document is not about an AI/ML device.

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The device is made from PMMA (polymethylmethacrylate) for the fabrication of temporary crowns and bridges and is intended for use in the oral cavity for up to six (6) months while awaiting a permanent restorations are designed and manufactured by a dental Professional (Technician) using CAD technology.

The PMMA Blocks for Dental Use is a homogeneous high polymer material made from PMMA (polymethylmethacrylate) added with cross-linking agents to improve the network structure through a unique polymerization molding technology. The device is for the fabrication of temporary crowns and bridges and is intended for use in the oral cavity for up to six months while awaiting a permanent restorations are designed and manufactured by a dental professional (such as a dentist) using CAD technology.

The proposed device contains two models with different shape: Cylinder and Cuboid. There are 39 specifications for Cylinder model (variation in different diameters and heights), and 44 specifications for Cuboid model (variation in different lengths, widths, and heights).

There are 20 various shades of the proposed device: 1 is transparent (without color added), the other 19 shades are colored (with different coloring matters added). The 19 shades created based on 19 Vita Shades contain A1, A2, A3, A3.5, A4, B1, B2, B3, B4, C1, C2, C3, C4, D2, D3, D4 and OM1,OM2,OM3.

The PMMA Blocks for Dental Use would be produced on the 39 specifications of Cylinder model or 44 specifications of Cuboid model, with a shade chosen from the 20 various shades.

The PMMA Blocks for Dental Use is provided as non-sterile.

This document describes acceptance criteria and provides results from non-clinical testing of "PMMA Blocks for Dental Use". The document does not contain information about a study that proves the device meets the acceptance criteria, nor does it contain information about clinical studies with human readers or AI.

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly present a table of acceptance criteria with corresponding device performance values against those criteria. Instead, it refers to compliance with international standards for performance and biocompatibility.

Performance Test Standards:

2. Sample Size Used for the Test Set and Data Provenance

The document describes non-clinical testing of a dental material. Information regarding "sample size used for the test set" typically refers to the number of individual test specimens or batches tested for each specific test mentioned (e.g., number of specimens for flexural strength, number of samples for cytotoxicity assay). However, this specific detail (the exact number of specimens per test) is not provided in the document.

Data provenance (country of origin, retrospective/prospective) is not applicable in the context of this non-clinical, in-vitro/materials testing. The tests are laboratory-based and performed on the device material itself, not on patient data.

3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications of Those Experts

This information is not applicable as the document describes non-clinical material testing, not human-reviewed data where "ground truth" would be established by experts.

4. Adjudication Method for the Test Set

This information is not applicable as the document describes non-clinical material testing, not a study involving human interpretation or adjudication.

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

An MRMC comparative effectiveness study was not done. The document focuses on the non-clinical performance and biocompatibility of a dental material, not on the effectiveness of human readers or AI assistance.

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

A standalone algorithm performance study was not done. The device is a material, not a software algorithm.

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

This information is not applicable as the document pertains to non-clinical material testing, where "ground truth" is typically defined by scientific measurement against established standards (e.g., specific chemical composition, physical properties, or biological reactions measured in a lab setting), rather than clinical interpretation or outcomes.

8. The sample size for the training set

This information is not applicable. The document describes the testing of a physical medical device (PMMA Blocks), not an AI algorithm that would require a training set.

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

This information is not applicable. As in point 8, there is no training set mentioned or implied in this document.

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