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Green X 12 SE (Model : PHT-40CHS) is intended to produce panoramic, cephalometric, or 3D digital x-ray images. It provides diagnostic details of the dento-maxillofacial, sinus, and TMJ for adult and pediatric patients. The system also utilizes carpal images for orthodontic treatment. The device is to be operated by healthcare professionals.

Green X 12 SE (Model : PHT-40CHS) is an advanced 4-in-1 digital X-ray imaging system that incorporates PANO, CEPH(optional), CBCT and MODEL Scan imaging capabilities into a single system. Green X 12 SE (Model : PHT-40CHS), a digital radiographic imaging system, acquires and processes multi-FOV diagnostic images for dentists. Designed explicitly for dental radiography. Green X 12 SE (Model : PHT-40CHS) is a complete digital X-ray system equipped with imaging viewers, an X-ray generator and a dedicated SSXI detector. The digital CBCT system is based on a CMOS digital X-ray detector. The CMOS CT detector is used to capture 3D radiographic images of the head, neck, oral surgery, implant and orthodontic treatment. Green X 12 SE (Model : PHT-40CHS) can also acquire 2D diagnostic image data in conventional PANO and CEPH modes.

The provided document does not contain information regarding a study that proves the device meets specific acceptance criteria in the context of AI performance, clinical trials, or comparative effectiveness studies with human readers. The document describes a Computed Tomography X-Ray System named Green X 12 SE (PHT-40CHS) and its substantial equivalence to a predicate device (Green X 12 (PHT-75CHS)).

The performance data section primarily focuses on:

• Substantial Equivalence: Demonstrating that the new device is equivalent to the predicate device despite minor changes in detector technology and some feature deletions.
• Technical Performance Testing: Verification against international standards (IEC 61223-3-5) for general image quality indicators like Contrast, Noise, CNR, and MTF, and dosimetric performance (DAP).
• Safety and EMC: Compliance with relevant IEC standards for electrical, mechanical, environmental safety, and electromagnetic compatibility.
• Software Verification and Validation: Adherence to FDA guidance for device software functions.

Therefore, many of the requested categories for AI-related studies and acceptance criteria are not applicable based on the provided text.

Here's a breakdown of the available information:

1. Table of Acceptance Criteria and Reported Device Performance:

The document does not explicitly state "acceptance criteria" in a table format for AI performance. Instead, it refers to equivalence to a predicate device and compliance with international performance standards for Computed Tomography X-ray systems.

2. Sample size used for the test set and the data provenance: Not applicable. The document discusses bench testing and comparison to a predicate device, not a test set of patient cases for AI evaluation.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable. This information is relevant for AI (CAD) performance studies, which are not described here.

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set: Not applicable.

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 was described. The device is an X-ray imaging system, not an AI-assisted diagnostic tool in the sense of a CADe/CADx system.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not applicable. The device is a physical imaging system.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.): Not applicable in the context of AI performance. For the technical performance aspects, the "ground truth" would be established by the specifications and measurements according to IEC standards.

8. The sample size for the training set: Not applicable. This device is an imaging system, not an AI algorithm requiring a training set in the conventional sense.

9. How the ground truth for the training set was established: Not applicable.

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The Green Card Bowie-Dick Test is designed to detect the presence of residual air in pre-vacuum steam sterilizers operating at 270°F (132°C) and 273°F (134°C) for 3.5 minutes. The indicator will demonstrate a uniform color change from purple to green when the proper sterilization conditions are met and no air is present. If enough air is present to create a 2°C or greater temperature difference in a standard Bowie-Dick test towel pack, the indicator will demonstrate a non-uniform color change.

The Green Card Bowie-Dick Test is designed specifically for daily monitoring of pre-vacuum steam sterilizers to detect the presence of residual air as recommended by ANSI/AAMI ST79: Comprehensive Guide to Steam Sterilization and Sterility Assurance in Health Care Facilities. The Green Card Bowie-Dick Test is a 3.5" X 1.91" card with the indicator ink printed on one side. Both sides of the card are laminated with a polyester film and an identification/record label is placed on the back side. The Green Card Bowie-Dick Test duplicates the resistance of a Bowie-Dick towel pack as described in ANSI/AAMI ST8 Hospital Steam Sterilizers.

The Green Card Bowie-Dick Test indicator areas will uniformly change color from purple to green when a passing Bowie-Dick test is performed. If a significant amount of air is present inside the sterilizer chamber during the sterilization cycle, it will be detected by the Green Card and displayed as a purple area on the indicator card, whereas the remainder of the indicator will have turned green. The non-uniform color change demonstrates the presence of air that would have created a 2°C temperature depression in a standard cloth Bowie-Dick pack.

The provided text describes the Green Card Bowie-Dick Test (BD115), a sterilization process indicator. The study detailed is a non-clinical performance test to verify the device meets applicable standards for Class 2 indicators for Bowie and Dick-type air removal tests.

Here's the breakdown of the acceptance criteria and study proving device performance:

1. Table of Acceptance Criteria and Reported Device Performance:

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

• Sample Size: The testing was conducted on 3 manufactured lots of the Green Card Bowie-Dick Test.
• Data Provenance: The document does not specify the country of origin for the data or whether it was retrospective or prospective. Given the nature of a 510(k) submission for a physical device, it's highly likely to be prospective testing conducted by the manufacturer (SteriTec Products, Inc., located in Englewood, CO, USA).

3. Number of Experts Used to Establish Ground Truth and Qualifications:

• This information is not provided in the document. The ground truth for this type of device (a chemical indicator for sterilization) is established through physical measurements of temperature and air presence in a controlled sterilization environment, not through expert interpretation of images. The criteria refer to thermocouple graphs for temperature verification.

4. Adjudication Method for the Test Set:

• Not applicable or not specified. The performance of this device is assessed against objective physical and chemical changes (color change, temperature differences) based on defined ANSI/AAMI/ISO standards, rather than subjective human interpretation requiring adjudication.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study:

• No. This type of study is not relevant for this device. An MRMC study is typically performed for AI/image analysis systems where human readers interpret medical images, and the AI assists in that interpretation. The Green Card Bowie-Dick Test is a chemical indicator that provides a direct visual result.

6. Standalone (Algorithm Only Without Human-in-the-Loop Performance) Study:

• Yes, effectively. The performance testing described is for the device itself to objectively meet specific physical and chemical criteria. The "algorithm" here is the chemical reaction of the indicator. The acceptance criteria are based on whether the indicator changes color as expected under specific sterilization conditions, without human interpretation influencing the measurement of those conditions (e.g., thermocouple readings). The visual interpretation of the color change by a human is the final step, but the "performance" of the device in demonstrating the condition is intrinsic to the device itself.

7. Type of Ground Truth Used:

• The ground truth is established through objective physical measurements in controlled sterilization environments, specifically:
  • Temperature measurements using thermocouples within a "Standard Test Pack" and at the drain, to verify specific temperature differences (e.g., no greater than 0.5°C difference for pass, 2°C or greater for fail).
  • Defined steam sterilization cycles (e.g., 270°F/132°C and 273°F/134°C for 3.5 minutes).
  • Absence or presence of residual air engineered into the test conditions.
  • Direct observation of color change (uniform green for pass, non-uniform with purple for fail) and color density as per ANSI/AAMI/ISO standards.

8. Sample Size for the Training Set:

• Not applicable/Not specified. This is a physical chemical indicator, not an AI/machine learning algorithm that requires a "training set" in the computational sense. Its performance is inherent to its material composition and design, which is validated through a test set of manufactured lots.

9. How the Ground Truth for the Training Set Was Established:

• Not applicable. As explained above, there is no "training set" for this device in the context of an AI/ML algorithm. The device's inherent chemical and physical properties are designed to react to specific sterilization conditions, and its performance is validated against established industry standards for those reactions, not "trained" on data.

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Green X 21 (Model: PHT-90CHO) is intended to produce panoramic, cephalometric, or 3D digital Xray images. It provides diagnostic details of the dento-maxillofacial, sinus, TMJ, and ENT for adult and pediatric patients. The system also utilizes carpal images for orthodontic treatment. The device is to be operated by healthcare professionals.

Green X 21 (Model : PHT-90CHO) is an advanced 6-in-1 digital X-ray system specifically designed for 2D and 3D dental radiography. This system features six imaging modalities: PANO, CEPH (optional), DENTAL CT, ENT CT, MODEL, and FACE SCAN, all integrated into a single unit.

Green X 21's imaging system is based on digital TFT detectors, accompanied by imaging viewers and an X-ray generator.

The materials, safety characteristics, X-ray source, indications for use and image reconstruction/MAR(Metal Artifact Reduction) algorithm of the subject device are same as the predicate device (PHT-75CHS (K210329)). The subject device differs from the predicate device in the following ways: It is equipped with new X-ray detectors for CT/PANO and CEPH modification results in a different maximum FOV provided in a single scan for CT mode compared to the predicate device. For CEPH modality, the subject device utilizes a one- shot imaging capture method.

Additionally, the subject device includes new modalities such as ENT CT and FACE SCAN with a face scanner, along with new software functions, including Auto Pano, Smart Focus, and Scout.

The provided document describes a 510(k) premarket notification for the "Green X 21 (PHT-90CHO)" digital X-ray system. The core of the submission is to demonstrate substantial equivalence to a predicate device, the "Green X 18 (PHT-75CHS)". The document focuses heavily on comparing technical specifications and performance data to support this claim, particularly for the new components and features of the Green X 21.

However, it's crucial to note that this document does not describe a study that proves the device meets specific acceptance criteria in the context of an AI/human-in-the-loop performance study. Instead, it focuses on engineering performance criteria related to image quality and safety for an X-ray imaging device, and comparing these to a predicate device. The "acceptance criteria" discussed are primarily technical specifications and performance benchmarks for the X-ray system components (detectors, imaging quality metrics), rather than clinical performance metrics in disease detection with AI assistance.

Therefore, many of the requested items (e.g., sample size for test set, number of experts for ground truth, adjudication method, MRMC study, standalone performance) are not applicable or not detailed in this submission because the device in question is an X-ray imaging system, not an AI-based diagnostic tool. The "new software functions" mentioned (Auto Pano, Smart Focus, Scout) are described as image reconstruction or manipulation tools, not AI algorithms for clinical diagnosis.

Here's a breakdown based on the information available, addressing the points where possible and noting when information is absent or not relevant to the provided text:

Acceptance Criteria and Reported Device Performance

Given that this is an X-ray imaging device and not an AI diagnostic tool, the acceptance criteria are generally related to image quality, safety, and functional performance, benchmarked against standards and the predicate device.

Table of Acceptance Criteria and Reported Device Performance (as inferred from the document):

Study Details (as far as applicable and available)

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

   • Test Set Description: The "test set" in this context is referring to data collected through bench testing using phantoms for image quality assessment, and potentially clinical images for subjective comparison, rather than a clinical trial cohort.
   • Sample Size: Not specified in terms of number of patient images. The testing was conducted on the device itself using phantom studies (e.g., test patterns for MTF, line pairs for resolution, phantoms for low contrast).
   • Data Provenance: The bench tests were conducted in a laboratory ("in a laboratory using the same test protocol as the predicate device"). The "Clinical consideration" section for image quality evaluation implies some clinical image review, but the origin (e.g., country, retrospective/prospective) of these potential clinical images is not detailed.

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

   • Not Applicable in the traditional sense of an AI study. Ground truth for an X-ray imaging device's performance is typically established through quantitative measurements using phantoms and technical specifications, not expert consensus on medical findings.
   • The document mentions "Image Quality Evaluation Report and Clinical consideration" and concludes "the subject device performed equivalently or better than the predicate device in overall image quality." This implies some form of expert review for subjective image quality, but the number or qualifications of these "experts" are not detailed.

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

   • Not Applicable. As noted above, this is not an AI diagnostic study with a human-in-the-loop component requiring adjudication of disease findings. The evaluations are primarily technical and quantitative measurements comparing physical properties and image output.

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:

   • No. An MRMC study was not described. This is an X-ray imaging system, not an AI diagnostic software that assists human readers. The new software functions (Auto Pano, Smart Focus, Scout) described are image manipulation/reconstruction features, not AI for diagnostic assistance.

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

   • Not applicable in the context of an AI algorithm. The device is an X-ray system; its "standalone" performance refers to its ability to produce images according to technical specifications, which was assessed through bench testing (MTF, DQE, NPS, etc.). There is no mention of a diagnostic AI algorithm that operates standalone.

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

   • Quantitative Phantom Measurements and Technical Specifications: For image quality (MTF, DQE, NPS, line pair resolution, contrast, noise, CNR), the ground truth is established by physical measurements using standardized phantoms and reference values as per IEC standards.
   • Predicate Device Performance: A key "ground truth" for substantial equivalence is the established performance of the predicate device. The new device's performance is compared against this benchmark.
   • Internal Criteria: For functionalities like FACE SCAN, "internally established criteria" were used as a benchmark.

7. The sample size for the training set:

   • Not Applicable. This document describes an X-ray imaging device, not an AI model that requires a training set. The software functions mentioned (Auto Pano, Smart Focus, Scout) are described as computational algorithms for image reconstruction or enhancement, not machine learning models that learn from a training dataset.

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

   • Not Applicable. No training set for an AI model is described.

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The GREENS BRAND Posterior, Non-cervical Pedicle Screw Spinal System is a pedicle screw fixation system intended for immobilization and stabilization of spinal segments in skeletally mature patients as an adjunct to fusion in the treatment of the following acute and chronic instabilities or deformities of the thoracic, lumbar, and sacral spine: · Degenerative disc disease (defined as discogenic back pain with degeneration of the disc confirmed by history and radiographic studies) - · Spondylolisthesis - · Trauma (e.g., fracture or dislocation) - · Deformity or curvature (e.g., scoliosis, kyphosis, and/or lordosis) - Tumor - · Spinal stenosis - · Pseudarthrosis - · Failed previous fusion Paediatric Use: When used for posterior non-cervical screw fixation in paediatric patients, the GREENS BRAND Posterior, Non-cervical Pedicle Screw Spinal System is indicated as an adjunct to treat adolescent idiopathic scoliosis. Additionally, it is intended to treat paediatric patients diagnosed with the following conditions: - · Spondylolisthesis - · Spondylolysis - Fracture caused by tumor and/or trauma. Paediatric pedicle screw fixation is limited to a posterior approach and is intended to be used with autograft and/or allograft.

The posterior non-cervical pedicle screw spinal system consists of a body, bushing, and ball head screw. Inner Screw, rods complete the spinal construct. The body portion of the screw rotates about the ball head on the screw, which provides increased motion over a fixed post of the polyaxial screw. An increase in motion facilitates the capture of rods that are not perfectly aligned. The Screws, Rods are fabricated from Titanium alloy. These implants are supplied non-sterile; the products have to be sterilized prior to use.

This document is a 510(k) Pre-market Notification for a medical device called the "GREENS BRAND Posterior, Non-cervical Pedicle Screw Spinal System." It is a submission to the FDA seeking clearance to market this device, demonstrating its substantial equivalence to already legally marketed predicate devices.

The document does not describe or conduct a clinical study with acceptance criteria related to a device's performance in diagnosing or treating patients using metrics like sensitivity, specificity, or accuracy.

Instead, this submission focuses on demonstrating substantial equivalence to existing predicate devices based on:

• Indications for Use: The intended medical conditions the device will treat.
• Material: The materials used in its construction.
• Mechanical Performance: How the device functions under various physical stresses.
• Dimensions: The physical size and shape of the device components.

The "acceptance criteria" discussed in this document refer to the performance standards that the device must meet to demonstrate its mechanical integrity and safety, not its clinical effectiveness in human subjects.

Here's a breakdown of the requested information based on the provided document:

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

The document does not provide a table with specific quantitative acceptance criteria values (e.g., specific load limits, displacement thresholds) and reported device performance values for a clinical study. Instead, it refers to compliance with established ASTM standards for mechanical testing. For the purpose of this type of submission, compliance with these standards serves as the "acceptance criteria" for mechanical performance.

Note: "Demonstrated performance" in this context means the device met the requirements of these standards. The document does not provide the specific numerical results of these tests, only that the device "has been demonstrated using the following performance testing" and "complied to following material standard."

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 as the submission relies on non-clinical mechanical testing of the device components, not on a clinical test set from human subjects. The "samples" would be the manufactured implant components themselves, and the testing is performed in a laboratory setting. There is no mention of data provenance in terms of country of origin or retrospective/prospective data collection for clinical outcomes.

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. Ground truth, in the context of clinical studies (e.g., for diagnostic accuracy), would typically be established by clinical experts. Since this submission focuses on mechanical and material equivalence, such experts are not involved in defining "ground truth" for the device's physical properties. The "ground truth" for mechanical properties is established by the ASTM standards themselves.

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

This information is not applicable. Adjudication methods are used in clinical studies, particularly for diagnostic imaging, to resolve discrepancies among expert readers. As this is a mechanical testing submission, no such adjudication method is used.

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. This type of study is relevant for AI or diagnostic devices involving human interpretation of results, which is not the subject of this 510(k) submission. Therefore, there is no effect size reported.

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

This information is not applicable. This is a physical medical implant (pedicle screw system), not an algorithm or a software device, so the concept of standalone algorithm performance does not apply.

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

The "ground truth" for this device's mechanical and material properties is established by compliance with the internationally recognized ASTM material and performance standards (ASTM F136, ASTM F1717, ASTM F1798). These standards define the acceptable physical and mechanical characteristics for such spinal implants.

8. The sample size for the training set

This information is not applicable. This is a physical medical implant, not a machine learning or AI device that requires a training set.

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

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

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Green Non Sterile Powder Free Nitrile Examination Gloves is a disposable device intended for medical purposes that is worn on the examiner's hand to prevent contamination between patient and examiner.

Green Non Sterile Powder Free Nitrile Examination Gloves

The provided text is a 510(k) clearance letter from the FDA for "Green Non Sterile Powder Free Nitrile Examination Gloves." This document is a regulatory communication for a medical device and does not contain information regarding an AI/ML medical device, clinical study results, or performance criteria as would be relevant for devices that use algorithms or sophisticated analytical methods.

Therefore, I cannot extract the requested information (acceptance criteria, study details, expert qualifications, adjudication methods, MRMC studies, standalone performance, ground truth details, or training set information) because this information is not present in the provided FDA clearance letter for examination gloves.

The letter confirms that the device is substantially equivalent to legally marketed predicate devices and is subject to general controls, but it does not detail performance studies or criteria relevant to AI/ML devices.

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The Green OR Reprocessed Aquamantys Bipolar Sealer is a sterile, single-use bipolar electrosurgical device intended to be used in conjunction with a qualified Pump Generator for delivery of radio-frequency (RF) energy and saline for hemostatic sealing and coagulation of soft tissue and bone at the operative site. The device is not intended for contraceptive tubal coagulation (permanent female sterilization).

The Green OR Reprocessed Aquamantys 2.3 Bipolar Sealer is intended for, but not limited to orthopaedic, neurosurgical, spine, thoracic, and open abdominal surgery.

The Green OR Reprocessed Aquamantys 6.0 Bipolar Sealer is intended for, but not limited to orthopaedic, spine, thoracic, and open abdominal surgery.

The Green OR Reprocessed Aquamantys 9.5 XL Bipolar Sealer is intended for, but not limited to open abdominal, orthopaedic, and thoracic surgery.

Not Found

This document is a 510(k) Pre-market Notification for a reprocessed medical device, the Green OR Reprocessed Aquamantys Bipolar Sealer. The submission aims to demonstrate substantial equivalence to the original, legally marketed predicate devices.

1. Table of Acceptance Criteria and the Reported Device Performance:

The document lists performance testing conducted to demonstrate substantial equivalence. These tests serve as the "acceptance criteria" for the reprocessed device to perform comparably to the original. The document states that the functional characteristics "have been evaluated and found to be equivalent to the predicate devices."

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

The document does not explicitly state the sample sizes used for each specific test. It broadly refers to "the functional characteristics of the subject devices have been evaluated." As this is a 510(k) for a reprocessed device, the data provenance would primarily be from laboratory testing conducted on the reprocessed units, comparing them against the specifications or performance of new, original devices (the predicates). There is no mention of clinical data or patient data (retrospective or prospective) in this summary.

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

This type of information (number and qualifications of experts) is typically associated with studies involving human interpretation or clinical outcomes, such as imaging diagnostic algorithms. For a device like a bipolar sealer undergoing functional and safety testing, the "ground truth" is established by objective engineering and laboratory standards and measurements, not expert human interpretation. Therefore, this information is not applicable or provided in this type of submission.

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

Adjudication methods like 2+1 or 3+1 are used to resolve disagreements among human experts in cases of subjective interpretation (e.g., radiology reads). Since the described tests are objective laboratory and engineering assessments of device performance (e.g., RF power output, residual protein), such an adjudication method is not relevant or applied.

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 is used to evaluate the diagnostic performance of humans, often with and without AI assistance, on a set of cases. This device (a reprocessed bipolar sealer) is a surgical tool, not a diagnostic imaging device typically associated with human "readers" or AI assistance in a diagnostic context. Therefore, an MRMC study was not conducted, and effect sizes related to human reader improvement with AI assistance are not applicable.

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

This device is not an algorithm or an AI system, but a physical electrosurgical tool. Therefore, the concept of "standalone" performance for an algorithm is not applicable. The performance testing described (RF power, saline flow, cleaning, etc.) is the "standalone" performance of the reprocessed device itself.

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

For the specific tests listed (RF Power Output, Saline Flow Rate, Biocompatibility, Sterilization, Cleaning, Electrical Safety), the ground truth is established by objective, measurable engineering specifications, industry standards (e.g., IEC 60601-2-2), and validated test methods. For example, RF power output would be measured against the manufacturer's specified output range for a new device, and residual protein levels would be measured against established acceptance limits. It would not typically involve expert consensus, pathology, or outcomes data in the usual sense for this type of device and testing.

8. The sample size for the training set:

As this is a reprocessed physical medical device and not an AI/ML algorithm, the concept of a "training set" is not applicable. The device itself is manufactured/reprocessed and then tested, not "trained."

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

Since there is no "training set" for this device, this question is not applicable.

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Green X 18 (Model : PHT-75CHS) is intended to produce panoramic, cephalometric or 3D digital x-ray images. It provides diagnostic details of the dento-maxillofacial, ENT, sinus and TMJ for adult and pediatric patients. The system also utilizes carpal images for orthodontic treatment. The device is to be operated by healthcare professionals.

Green X 18 (Model : PHT-75CHS) is an advanced 4-in-1 digital X-ray imaging system that incorporates PANO, CEPH(optional), CBCT and MODEL Scan imaging capabilities into a single system. Green X 18 (Model : PHT-75CHS), a digital radiographic imaging system, acquires and processes multi-FOV diagnostic images for dentists. Designed explicitly for dental radiography. Green X 18 (Model : PHT-75CHS) is a complete digital X-ray system equipped with imaging viewers, an X-ray generator and a dedicated SSXI detector. The digital CBCT system is based on a CMOS digital X-ray detector. The CMOS CT detector is used to capture 3D radiographic images of the head, neck, oral surgery, implant and orthodontic treatment. The materials, safety characteristics, X-ray source, indications for use and image reconstruction/MAR(Metal Artifact Reduction) algorithm of the subject device are same to the predicate device (PHT-75CHS (K201627)). The difference from the predicate device is that it is equipped with a new CBCT/PANO detector to provide users with a larger CBCT FOV.

The medical device in question is the Green X 18 (Model: PHT-75CHS), a digital X-ray imaging system for panoramic, cephalometric, and 3D dental imaging. The study described focuses on demonstrating substantial equivalence to a predicate device, the Green X (Model: PHT-75CHS, K201627), particularly concerning a new detector, Xmaru1524CF Master Plus OP.

Based on the provided text, the acceptance criteria and study information can be summarized as follows:

1. Table of Acceptance Criteria and Reported Device Performance:

The document primarily focuses on demonstrating equivalence to the predicate device rather than setting specific numeric acceptance criteria for unique features or diagnostic accuracy. Instead, the acceptance is based on the new detector performing "equivalently or better" than the predicate.

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

• Sample Size: Not explicitly stated as a number of patient cases or images. The performance testing was conducted in a laboratory setting using test protocols and phantoms, not a clinical test set of patient images.
• Data Provenance: The testing was "non-clinical" and "in a laboratory." It compared the performance of the new detector and the subject device against the predicate device. This implies retrospective comparison against previously established performance data for the predicate, and possibly prospective bench testing on the new device itself. The data is likely from the manufacturer's internal testing facilities (presumably in Korea, given the manufacturer's address).

3. Number of Experts and Qualifications for Ground Truth of Test Set:

• There is no mention of human experts being used to establish ground truth for a test set of clinical images. The provided information describes non-clinical performance testing using quantitative metrics (DQE, MTF, NPS, Contrast, Noise, CNR) and comparison to the predicate device, as well as a "Clinical consideration and Image Quality Evaluation Report" which "demonstrated that the general image quality of the subject device is equivalent or better than the predicate device in PANO/CBCT mode." However, details on how this "Clinical consideration" was performed (e.g., blinded review by experts, number of experts, their qualifications, or what "ground truth" they used) are not provided in this summary.

4. Adjudication Method for the Test Set:

• Not applicable as the testing described is primarily non-clinical and does not involve human readers or a clinical test set requiring adjudication in the context of diagnostic accuracy.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study:

• No, a multi-reader multi-case (MRMC) comparative effectiveness study was not explicitly mentioned. The study focuses on equivalence through non-clinical performance metrics and comparison to a predicate device, not on how human readers' performance improves with or without the device.

6. Standalone Performance:

• Yes, performance data for the standalone device/detector was done. The document outlines bench testing of the Xmaru1524CF Master Plus OP detector and the Green X 18 system itself, measuring metrics such as pixel size, DQE, MTF, NPS, Contrast, Noise, CNR, and DAP. These measurements represent the algorithm-only/device-only performance in a controlled environment.

7. Type of Ground Truth Used:

• For the non-clinical performance testing, the "ground truth" was established by physical standards and quantitative measurements in a laboratory setting, comparing the device's performance against industry standards (e.g., 21 CFR Part 1020.30, 1020.33, IEC 61223-3-5, IEC 61223-3-4) and the performance of the predicate device.
• For the "Clinical consideration and Image Quality Evaluation Report," the method for establishing ground truth is not detailed, but it would presumably involve expert review of images obtained from the device.

8. Sample Size for the Training Set:

• No training set information is provided, as the submission describes a medical imaging device (X-ray system), not an AI algorithm that requires a training set of images. The "image reconstruction/MAR(Metal Artifact Reduction) algorithm" is mentioned as being the same as the predicate device, implying it was developed prior and is not a new algorithm requiring a new training study for this submission.

9. How the Ground Truth for the Training Set Was Established:

• Not applicable, as this is an imaging device and not an AI algorithm requiring a training set with established ground truth.

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The Greenmedi safety filter syringe is intended to inject the drug solutions into the human body. It is designed to prevent needle stick injuries. The 0.5um filter operates when into the human body to remove foreign substances from the drug solutions.

The Greenmedi safety filter syringe consists of a plunger that fits tightly within a barrel and a needle. The plunger can be linearly pulled and pushed along the inside of the tube, allowing the syringe to take in and expel liquid through a needle. After use, the health care professional fully depresses the Luer Assembly. Once the Luer Assembly is engaged, pulling back the plunger causes the Adapter and the attached needle to be withdrawn into the safety of the barrel. In this position against the flange, lateral pressure on the plunger results in a controlled fracture of the plunger. Both the syringe and plunger are discarded in a sharps container.

This is a 510(k) summary for a medical device called the Greenmedi Safety Filter Syringe. It does not contain information about an AI/ML powered device, therefore, the requested information cannot be extracted.

No AI/ML related information is present in the provided document.

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Greene Renal Transplant Stent Set is used to establish temporary internal drainage from the ureteropelvic junction to the bladder. It is indicated for use following renal transplant.

The Greene Renal Transplant Stent Set is sterile, single-use device. The Greene Renal Transplant Stent Set is comprised of a double pigtail multi-length silicone stent, a radiopaque polyurethane ureteral catheter, a vinyl stent positioner and a stainless steel wire guide. The stent is available in sizes, 6.0 and 7.0 Fr with multi-length 8 to 20 centimeters. The stents are constructed of radiopaque silicone elastomer. Sideports extend along the body of the stent as well as on the curled pigtail loops (pigtail) to provide drainage. The stents are secured in the urinary tract with pigtail loops on the proximal and distal ends. There are black ink markings at the proximal and distal ends, and grey ink marks on the stent body which provide visualization during stent advancement and placement. The Greene Renal Transplant Stent is labeled for a 3-month indwell time.

The set will be supplied sterilized by ethylene oxide gas in a peel-open package and intended for one-time use. The product is packaged with three-year shelf life.

This document is a 510(k) premarket notification for the Greene Renal Transplant Stent Set. It describes the device, its intended use, and comparative testing against a predicate device to demonstrate substantial equivalence. However, this document does not contain the detailed acceptance criteria and study proving device performance as typically expected for an AI/ML medical device submission.

This 510(k) is for a physical medical device (a ureteral stent), not a software or AI/ML product. The "Performance Data" section lists various physical and chemical tests conducted on the stent set (e.g., sterility, packaging, biocompatibility, stent radiopacity, curl retention, kink radius, flow rate, MRI compatibility). These are standard tests for physical medical devices to ensure their safety and functionality.

Therefore, I cannot extract the information required by your prompt, as it pertains to AI/ML device validation (e.g., sample sizes for test/training sets, expert ground truth, MRMC studies, standalone algorithm performance), which is not relevant to this type of device.

The document states: "The results of these tests provide reasonable assurance that the Greene Renal Transplant Ureteral Stent Set met the design input requirements based on the intended use. The subject device does not raise new questions of safety or effectiveness as compared to the predicate." This is the general conclusion of substantial equivalence for a physical device, based on the non-AI/ML specific performance tests listed.

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