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The Televere Digital Dental Imaging System is intended for radiographic examination by a dental professional to assist in the diagnosing of diseases of the teeth, jaw and oral structures. Not for mammography. Not for fluorosopy.

The Televere Digital Dental Imaging System is an extraoral digital x-ray system comprised of two previously cleared individual components: (1) an intraoral detector component (K162619) which connects to a PC via a USB port and (2) and image management software package (i.e., Tigerview Professional, K061035). The device detector comes in two sizes: 600mm² (Hamamatsu CMOS area image sensor, S11684-12) and 884mm² (Hamamatsu CMOS area image sensor, S116845-12). X-ray generators that can integrate with the Televere Digital Dental Imaging System are wall-mounted x-ray generators (both AC and DC) with a tube current between 1 and 15mA inclusive, and with a tube voltage between 50 and 100kV inclusive, with built in controls to set exposure parameters. Generators allow variable mA/kV to be selected, all will control the exposure time. The device and software cannot act as an x-ray generator controller. All control of xray generation is done by controls built into the generator itself. There is no connection between the device and the x-ray generator. The device is an x-ray receiver and does not control the generator.

The provided text describes a 510(k) premarket notification for the "Televere Digital Dental Imaging System." The application aims to demonstrate substantial equivalence to a legally marketed predicate device rather than undergoing a de novo classification or a PMA. As such, the information provided focuses on the device's technical specifications and how they compare to the predicate, rather than detailed acceptance criteria and a "study" in the traditional clinical trial sense with statistical performance metrics against a defined ground truth.

Here's an analysis of the provided text in the context of your request:

Key Takeaway: This submission is a 510(k) for a digital dental imaging system (hardware + software), where the primary demonstration of safety and effectiveness relies on showing substantial equivalence to existing cleared components (an intraoral detector and image management software). It's not a diagnostic AI/CAD device that interprets images or provides a diagnosis, and therefore, the testing described is not a performance study against a clinical ground truth for diagnostic accuracy.

Based on the provided document, here's what can be inferred/extracted regarding acceptance criteria and "study" that proves the device meets them:

The "acceptance criteria" in this context are implicitly that the new device is as safe and effective as the predicate device and raises no new technical issues of safety or effectiveness. The "study" isn't a complex MRMC or standalone performance study measuring diagnostic accuracy of an AI, but rather a demonstration of technical equivalence and image quality to show non-inferiority.

1. Table of Acceptance Criteria and Reported Device Performance

Strictly speaking, the document does not present acceptance criteria in a quantitative, pre-defined table with numerical targets for diagnostic performance (e.g., sensitivity, specificity, AUC) because it's a 510(k) for an imaging system, not a diagnostic AI.

Instead, the "acceptance criteria" are qualitative and comparative:

• Safety and Effectiveness: "new device is as safe and effective as the predicate device."
• Image Quality: "Clinical images highlight equal or better image quality as compared to the predicate."
• No New Technical Issues: "no new technical issues of safety or effectiveness raised by substitution of the imaging software component."
• Clinical Acceptability: "Professional evaluation of imaging samples were of excellent quality, high resolution, clinically acceptable and substantially equivalent to the predicate device."

Reported Device Performance (Comparative):

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

• Test Set Sample Size: The document mentions "Sample clinical images from the new device were also provided" but does not specify the exact number of images/cases. It states they "were not necessary to demonstrate substantial equivalence," implying a limited set or perhaps general examples rather than a statistically powered test set for diagnostic accuracy.
• Data Provenance: Not specified (country of origin). The document does not indicate if the data was retrospective or prospective. Given the nature of a 510(k) for an imaging system, it's likely pre-existing generic clinical images or images taken during testing.

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

• Number of Experts: Not explicitly stated. The document refers to "Professional evaluation of imaging samples," which implies at least one, but no specific number is given.
• Qualifications of Experts: Not specified beyond "Professional evaluation." It's assumed to be dental professionals as per the device's indications for use.

4. Adjudication Method for the Test Set

• Adjudication Method: Not applicable/not described. This level of detail in adjudication (e.g., 2+1, 3+1) is typically associated with studies establishing ground truth for diagnostic AI, which is not the primary purpose of this 510(k). The evaluation appears to be a qualitative assessment of image quality for substantial equivalence.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was Done

• MRMC Study: No, an MRMC comparative effectiveness study was not done or described. The submission is focused on demonstrating substantial equivalence of an imaging system, not the diagnostic performance improvement of human readers using an AI algorithm.

6. If a Standalone (i.e., Algorithm Only Without Human-in-the-Loop Performance) Was Done

• Standalone Performance: Not applicable. This device is an imaging system (hardware and software), not an AI algorithm designed to generate a diagnosis or detection result on its own. The "software" component (Tigerview Professional) is a PACS-like image management software with basic adjustment features, not a diagnostic AI.

7. The Type of Ground Truth Used

• Type of Ground Truth: The concept of "ground truth" as a clinical diagnosis confirmed by pathology or outcomes data is not applicable here. The "ground truth" (or basis for comparison) was the clinical acceptability and image quality of the predicate device. The new device's images were evaluated against the expectation of quality for dental X-ray images and in comparison to what the predicate device produces. This is a qualitative assessment of imaging system performance, not diagnostic accuracy.

8. The Sample Size for the Training Set

• Training Set Sample Size: Not applicable. This is not a machine learning/AI device where a training set is used to develop an algorithm. The software component, Tigerview Professional, is a previously cleared PACS software (K061035) and is "unchanged" for this new device.

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

• Ground Truth for Training Set: Not applicable, for the same reasons as #8. There is no mention of an algorithm being trained, hence no training set ground truth established.

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The Televere Podiatry X-Ray System HF is intended for use by qualified clinicians for the x-ray of hands and feet. Not for mammography. Not fluoroscopy.

The Televere Podiatry X-Ray System HF consists of a combination of previously cleared Tigerview digital imaging software (K061035), a high frequency X-Ray generator (X-CEL MODEL HF 718BD, K160857), a PC-based computer and a power supply. Tigerview software provides an exposure control upgrade of the previously cleared HF x-ray generator by replacing the manual touchscreen of the Predicate Device (K160857) with the Tigerview computer software interface. Tigerview software provides basic image adjustment features as well as x-ray exposure control settings. An image adjustment system allows the physician to acquire, display, edit (e.g., resize, adjust contrast, crop, etc.), review, store, print, and distribute medical images within a Picture Archiving and Communication System (PACS) environment. Tigerview software runs on standard PC-compatible computers and is compatible with capture devices which attach to the computer using a Network Adaptor, USB port, PCI slot, parallel port, memory card, S-video port on a video capture card, or SCSI card.

The provided text is a 510(k) premarket notification for the Televere Podiatry X-Ray System HF. It focuses on demonstrating substantial equivalence to a predicate device, rather than presenting a study to prove the device meets specific acceptance criteria for diagnostic performance.

Therefore, the document does not contain the detailed information required to fill out a table of acceptance criteria and reported device performance as it would for a new AI/CAD device. Specifically:

• No specific acceptance criteria for diagnostic performance are stated. The submission focuses on regulatory compliance and technical specifications.
• No numerical performance metrics (e.g., sensitivity, specificity, AUC) are reported for diagnostic tasks. The "device performance" mentioned refers to electrical and safety aspects.
• No information on sample size for test sets, data provenance, number or qualifications of experts for ground truth, adjudication methods, MRMC studies, standalone performance, or ground truth types (pathology, outcomes data) is provided. These are typical for studies assessing diagnostic accuracy.
• No information on training set sample size or how training ground truth was established is provided. This is because the device is an X-ray system, not a machine learning algorithm requiring a training set for diagnostic tasks.

The document states:

• "The results of clinical image inspection, bench, and laboratory test results demonstrate that the new device is as safe and effective as the predicate device. Clinical images highlight equal or better image quality as compared to the predicate." (Page 4, Section 6)
• "Sample clinical images from the new device were also provided however they were not necessary to demonstrate substantial equivalence." (Page 5, Section 8)

This indicates that clinical images were reviewed, but a formal study with detailed acceptance criteria and quantitative diagnostic performance metrics was not conducted or deemed necessary for this 510(k) submission, which primarily addresses hardware and software integration.

The "Acceptance Criteria" provided in the document relate to the technical performance of the X-ray system itself (e.g., kVp accuracy, mA accuracy, timer accuracy, reproducibility, leakage radiation) and compliance with various electrical safety and radiation standards. These are listed under "Performance Accuracy" and "X-ray Beam Quality Metrics" in the Substantial Equivalence Chart on Page 5.

Summary of available information related to performance/acceptance criteria:

Missing Information (as per your request, not available in the document):

1. Sample size used for the test set and the data provenance: Not applicable for a diagnostic performance study as described in the prompt. Clinical images were inspected, but details like sample size or origin for that inspection are not provided.
2. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable, as no formal diagnostic performance study is presented.
3. Adjudication method for the test set: Not applicable.
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, as this is solely an X-ray system, not an AI/CAD diagnostic aid.
5. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not applicable.
6. The type of ground truth used: For technical performance, the ground truth would be precise measurements and compliance with regulatory standards. For the "clinical image inspection," the ground truth would be expert visual assessment, but details are not provided.
7. The sample size for the training set: Not applicable, as this is an X-ray system, not a machine learning model.
8. How the ground truth for the training set was established: Not applicable.

In essence, the document serves as a regulatory submission demonstrating technical and safety equivalence, not a publication detailing a diagnostic performance study for a machine learning or CAD device.

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The Televere Podiatry Digital Imaging System is intended for digital image capture use in podiatry radiographic examinations, wherever conventional screen-film systems may be used. Not for mammography. Not for fluoroscopy.

The Televere Podiatry Digital Imaging System consists of a combination of digital imaging software, a flat panel display (FPD), a PC-based computer, and a power supply. The PC based computer, x-ray generator and the power-supply are necessary for a the subject device. The imaging software has previously been cleared by FDA (i.e., K061035, TigerView Professional) and is being used unchanged in the subject device. This previously cleared software provides basic image adjustment features - an image management system allowing the physician to acquire, display, edit (e.g., resize, adjust contrast, crop, etc.), review, store, print, and distribute medical images within a Picture Archiving and Communication System (PACS) environment. TigerView Professional runs on standard PC-compatible computers and is compatible with capture devices which attach to the computer using a Network Adaptor, USB port, PCI slot, parallel port, memory card, S-video port on a video capture card, or SCSI card. The FPD component seeking clearance (VarexPaxScan2530C) has not been previously cleared by FDA as an individual component. The FPD uses a large-area amorphous silicon sensor array with a gadolinium oxysulfide (GadOx) scintillator for displaying high quality images over a wide range of dose settings and is intended to be integrated into a complete X-ray system. This premarket notification seeks clearance for a combination finished device consisting of the combination of the previously cleared digital imaging software and the FPD component. The combination of the digital imaging software and the FPD does not affect the safety or efficacy of either component device alone, or in combination. A gigabit Ethernet port allows for tethered, non-wireless data transmission.

The provided document is a 510(k) premarket notification for the Televere Podiatry Digital Imaging System. It describes the device, its intended use, and a comparison to a predicate device to establish substantial equivalence. However, this document does not describe a study involving AI for image analysis.

Instead, it focuses on the physical and performance characteristics of a digital X-ray imaging system component (Flat Panel Display or FPD) and its integration with existing software. The "acceptance criteria" and "study that proves the device meets the acceptance criteria" in this context refer to the engineering and performance specifications of the imaging system and comparison to a legally marketed predicate device, rather than the performance of an AI algorithm against clinical ground truth.

Therefore, many of the requested items (e.g., sample size for test set, data provenance, number of experts for ground truth, MRMC study, standalone performance for AI, training set details) are not applicable for a 510(k) submission that doesn't involve an AI component that performs image analysis.

Based on the provided text, here's what can be extracted and what cannot:

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

The document doesn't explicitly state "acceptance criteria" in the format of pass/fail thresholds for clinical performance. Instead, it presents a "Substantial Equivalence Chart" which compares specifications of the new device to a predicate device. The implicit acceptance criteria are that the new device's performance metrics are "substantially equivalent" to the predicate.

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The Televere Digital Imaging System is intended for digital image capture use in general radiographic examinations, wherever conventional screen-film systems may be used. Allows imaging of the skull, chest, shoulders, pelvis, and extremities. Not for mammography.

The Televere Digital Imaging System consists of a combination of digital imaging software, a flat panel display (FPD), a PC-based computer and a power supply. The imaging software has previously been cleared by FDA (i.e., K061035, TigerView Professional). This previously cleared software provides basic image adjustment features: An image management system that allows the physician to acquire, display, edit (e.g., resize, adjust contrast, crop, etc.), review, store, print, and distribute medical images within a Picture Archiving and Communication System (PACS) environment. TigerView Professional runs on standard PCcompatible computers and is compatible with capture devices which attach to the computer using a Network Adaptor, USB port, PCI slot, parallel port, memory card, S-video port on a video capture card, or SCSI card. The FPD component seeking clearance (PerkinElmer Model XRPad 4343F N) has not been previously cleared by FDA. The FPD uses a large-area amorphous silicon sensor array with a gadolinium oxysulfide (GadOx) scintillator for displaying high quality images over a wide range of dose settings and is intended to be integrated into a complete X-ray system. This premarket notification seeks clearance for a combination finished device consisting of the combination of the previously cleared digital imaging software and the FPD. The combination of the digital imaging software and the FPD does not affect the safety or efficacy of either component device alone, or in combination.

The provided document is a 510(k) premarket notification for the Televere Digital Imaging System. It describes the device, its intended use, and proposes it as substantially equivalent to a predicate device.

Here's an analysis of the acceptance criteria and study information based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

The document doesn't explicitly state "acceptance criteria" in a numeric fashion other than stating the new device is "as safe and effective as the predicate device" and that "Clinical images collected demonstrate equal or better image quality as compared to our predicate." However, it does provide a comparative table with performance specifications of the new device against the predicate.

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

The document mentions "Sample clinical images from the new device were also provided however they were not necessary to demonstrate substantial equivalence." It does not specify a sample size for these clinical images, nor does it provide data provenance (country of origin, retrospective/prospective). The primary basis for substantial equivalence seems to be bench testing and comparison of technical specifications.

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

This information is not provided in the document. The substantial equivalence relies on physical and performance characteristic comparisons, not on expert-adjudicated clinical image interpretations for a test set to establish ground truth in the context of device performance metrics like sensitivity/specificity. The statement "Clinical images collected demonstrate equal or better image quality as compared to our predicate" suggests a qualitative assessment, but details about who made this assessment, how many, or their qualifications are absent.

4. Adjudication method for the test set

This information is not provided. Given that quantitative clinical ground truth was not the primary method for demonstrating substantial equivalence, formal adjudication methods are not detailed.

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, a multi-reader multi-case (MRMC) comparative effectiveness study was not done. The Televere Digital Imaging System is a digital X-ray receptor, not an AI-powered diagnostic tool. The purpose of the submission is to demonstrate substantial equivalence to a predicate X-ray system, primarily through technical specifications and bench testing, for image capture. There's no mention of AI or human reader improvement with or without AI assistance.

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

This question is not applicable as the device is an X-ray imaging system, not an algorithm, and does not operate independently in a diagnostic capacity without human interpretation.

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

For the technical performance metrics (MTF, DQE), the ground truth is established by physical measurements and standardized testing according to IEC standards and FDA guidance documents for solid-state digital X-ray panels. For the qualitative assessment of "clinical images," the type of ground truth and method of establishment is not explicitly stated, but it likely refers to a visual comparison of image quality, not a formal disease presence/absence ground truth.

8. The sample size for the training set

This information is not applicable as the Televere Digital Imaging System is a hardware device (digital X-ray receptor) and not a machine learning or AI algorithm that requires a training set.

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

This information is not applicable as the device is not an AI algorithm and does not use a training set.

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Visix Imaging is a clinical software application that receives images and data from various imaging sources (e.g., radiographic devices, digital video capture devices, and generic image devices such as scanners). Visix Imaging is intended to acquire, display, edit (e.g., resize, adjust contrast, annotate, etc.), review, store, print, and distribute images, plus store clinical notes in the form of annotations and measurements, using standard PC hardware. Visix Imaging is currently intended for dental use. It is not intended for mammography use.

Visix Imaging is an image management system that allows the physician to acquire, display, edit (e.g., resize, adjust contrast, etc.), review, store, print, and distribute medical images within a Picture Archiving and Communication System (PACS) environment. Visix Imaging runs on standard PC-compatible computers and is compatible with capture devices which attach to the computer using a USB port, parallel port, S-video port on a video capture card, or SCSI card.

The provided text is a 510(k) Summary for the Visix Imaging system, which is a Picture Archiving and Communication System (PACS). This document serves to demonstrate substantial equivalence to predicate devices, not to present a de novo study with acceptance criteria and a detailed performance evaluation of a new algorithm.

Here's a breakdown of why the requested information cannot be fully provided from the given text:

• Nature of the Submission: This is a 510(k) premarket notification. For devices like PACS, substantial equivalence is often established through technological comparison to legally marketed predicate devices, rather than extensive clinical efficacy studies with predefined acceptance criteria for AI algorithms. The "Testing" section explicitly states: "Visix Imaging has been demonstrated to perform as intended," which implies verification and validation activities (e.g., software testing, compatibility testing) against design specifications, but not a clinical performance study with statistical endpoints.
• Device Type: Visix Imaging is an image management system (PACS), designed to acquire, display, edit, review, store, print, and distribute medical images. It is not an AI diagnostic algorithm or a CAD (Computer-Aided Detection/Diagnosis) system that would typically require performance metrics like sensitivity, specificity, or AUC against a ground truth.

Therefore, most of the requested information regarding acceptance criteria, study design, sample sizes, ground truth, and expert involvement for an AI performance study is not available in this document because such a study was not conducted or required for this type of 510(k) submission.

However, I can extract the following information pertinent to the submission context:

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

• Acceptance Criteria: The document does not explicitly list quantitative acceptance criteria in terms of clinical performance metrics for an AI algorithm. The implicit acceptance criterion for this 510(k) submission is that the device is "substantially equivalent" to predicate devices, meaning it performs as intended as a PACS system with similar indications for use and technological characteristics.
• Reported Device Performance: "Visix Imaging has been demonstrated to perform as intended." This statement refers to the successful completion of verification and validation activities to ensure the software functions correctly as an image management system. No specific performance metrics (e.g., accuracy, sensitivity, specificity) against a clinical gold standard are provided for an AI component because it's not an AI diagnostic device in this context.

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

• Not Applicable / Not Provided: As this is a PACS system and not an AI diagnostic algorithm requiring a test set for performance evaluation against a ground truth, no such sample size or data provenance details are given. The "Testing" mentioned would have been internal software validation and verification.

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 / Not Provided: Ground truth establishment by experts is not described, as there was no clinical performance study of an AI algorithm in this submission.

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

• Not Applicable / Not Provided: No adjudication method is mentioned as there was no test set requiring expert adjudication for AI performance evaluation.

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 conducted or reported. The device is a PACS system, not an AI-assisted diagnostic tool for which such a study would be relevant.

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

• Not Applicable / Not Provided: This device is a PACS system; it's not presented as a standalone diagnostic algorithm.

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

• Not Applicable / Not Provided: No ground truth in the context of clinical disease status is mentioned, as there was no clinical validation study of an AI algorithm. For a PACS system, the "ground truth" would relate to its functionality, such as accurately displaying images or correctly performing edits, which are verified through software testing rather than clinical endpoints.

8. The sample size for the training set:

• NotApplicable / Not Provided: This document does not describe the development or training of an AI algorithm; therefore, no training set size is mentioned.

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

• Not Applicable / Not Provided: Not applicable for the reasons stated above.

Summary of Device and its Purpose based on the text:

• Device Name: Visix Imaging
• Classification Name: System, Image Processing, Radiological, 21 CFR 892.2050
• Intended Use: Acquire, display, edit (e.g., resize, adjust contrast, annotate), review, store, print, and distribute medical images, plus store clinical notes in the form of annotations and measurements, using standard PC hardware. Intended for dental use, not mammography.
• Technological Comparison (for substantial equivalence): Compared to Televere Systems' TigerView Professional (K061035), EagleSoft ChairSide Software Application (K982422), and Tau Corp.'s TigerScan/TigerView (K955237). All are software applications with similar indications for use and functions as PACS systems.
• Conclusion of 510(k) Notice: Visix Imaging is substantially equivalent to legally marketed Picture Archiving and Communications Systems.

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TigerView Professional is a clinical software application that receives images and data from various imaging sources (e.g., radiographic devices, digital video capture devices, and generic image devices such as scanners). In addition, TigerView Professional enables the storage of clinical notes, audio recordings, and clinical exam data.

It is intended to acquire, display, edit (e.g., resize, adjust contrast, crop, annotate, etc.), review, store, print, and distribute images using standard PC hardware.

TigerView Professional is an image management system that allows the physician to acquire, display, edit (e.g., resize, adjust contrast, crop, etc.), review, store, print, and distribute medical images within a Picture Archiving and Communication System (PACS) environment. TigerView Professional runs on standard PC-compatible computers and is compatible with capture devices which attach to the computer using a Network Adaptor, USB port, PCI slot, parallel port, memory card, S-video port on a video capture card, or SCSI card.

This 510(k) summary for Televere Systems TigerView Professional describes a Picture Archiving and Communication System (PACS) software. As such, the information provided focuses on its functional equivalence to predicate devices rather than clinical performance metrics typical of AI/ML-driven diagnostic devices.

Here's an analysis of the provided text based on your request:

Acceptance Criteria and Device Performance

The document does not explicitly state quantitative acceptance criteria or detailed device performance metrics in the way one would expect for a diagnostic algorithm. Instead, the "performance" is implicitly tied to demonstrating functional equivalence to predicate devices.

Study Details

Given the nature of this submission for a PACS system, a "study" in the clinical trial sense (with a test set, ground truth, and expert readers) is not described. The evaluation relies on demonstrating functional equivalence.

1. Sample size used for the test set and the data provenance: Not applicable/not specified. The "testing" mentioned is functional demonstration, not a clinical performance study with a test set of images.
2. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable/not specified. There is no mention of a ground truth established by experts for a test set.
3. Adjudication method (e.g., 2+1, 3+1, none) for the test set: Not applicable/not specified.
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 device is a PACS system, not an AI-driven diagnostic aid.
5. If a standalone (i.e., algorithm only without human-in-the-loop performance) was done: Not applicable. The device is a software platform, not a standalone diagnostic algorithm.
6. The type of ground truth used (expert consensus, pathology, outcomes data, etc.): Not applicable. The "ground truth" here is the functional performance of predicate devices, which the new device is compared against for substantial equivalence.
7. The sample size for the training set: Not applicable. As a PACS system, it doesn't involve machine learning model training in the conventional sense.
8. How the ground truth for the training set was established: Not applicable.

Conclusion based on the provided text:

The submission for Televere Systems TigerView Professional is a 510(k) for a Picture Archiving and Communication System (PACS). The "study" referenced in the document is a demonstration of functional equivalence to predicate PACS devices (EagleSoft ChairSide Software Application and TigerScan/TigerView), rather than a clinical performance study with defined acceptance criteria, test sets, or ground truth for diagnostic accuracy, which would be typical for an AI/ML-driven diagnostic device. The manufacturer states that "TigerView Professional has been demonstrated to perform as intended" and is "substantially equivalent to legally marketed Image Processing Systems (i.e. PACS)."

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